WIP OPTIMISATION FOR THE FOOD PROCESSING INDUSTRY

A case study of scheduling and Shop floor control methods

Bauwiena Visser

A thesis presented for the degree of:

MSc Technology & Operations managementand

MSc Operations & Supply chain Management

University of GroningenNewcastle Business University

Contents

1 Introduction 3

2 Theoretical background 52.1 Work in process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.2 Food processing industry . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.2.1 WIP in the Food Processing industry . . . . . . . . . . . . . . . . 72.3 Production Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2.3.1 Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.3.2 Tactical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92.3.3 Execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.4 Production control in FPI . . . . . . . . . . . . . . . . . . . . . . . . . . 92.4.1 Sequencing and scheduling . . . . . . . . . . . . . . . . . . . . . . 92.4.2 Sequencing rules . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.5 Shop Floor Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.6 Lean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.6.1 5S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142.6.2 Other visual aids . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

3 Methodology 163.1 Research questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163.2 Selection of methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163.3 Case study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173.4 Data collection and data analysis . . . . . . . . . . . . . . . . . . . . . . 173.5 Validation of effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . . 193.6 Validity and reliability . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

4 Analysis 204.1 Scheduling at the case-company . . . . . . . . . . . . . . . . . . . . . . . 20

4.1.1 Tactical decision: MPS . . . . . . . . . . . . . . . . . . . . . . . . 204.1.2 Production schedule . . . . . . . . . . . . . . . . . . . . . . . . . 204.1.3 Scheduling decisions . . . . . . . . . . . . . . . . . . . . . . . . . 22

4.2 Scheduling in the FPI . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234.2.1 Applying sequencing rules . . . . . . . . . . . . . . . . . . . . . . 244.2.2 Overall optimisation . . . . . . . . . . . . . . . . . . . . . . . . . 274.2.3 Additional optimisation . . . . . . . . . . . . . . . . . . . . . . . 28

4.3 Effectiveness of Shop Floor Control measures in the food industry . . . . 294.3.1 Material handling at the shop floor . . . . . . . . . . . . . . . . . 294.3.2 Classification of SFC-methods . . . . . . . . . . . . . . . . . . . . 314.3.3 Lean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

5 Validation 345.1 Drum-buffer-rope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345.2 Hybrid CONWIP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355.3 Hybrid two-boundary control system (TBC) . . . . . . . . . . . . . . . . 355.4 Minimal-blocking system . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

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5.5 Conclusion of validation . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

6 Discussion 386.1 Contribution to literature . . . . . . . . . . . . . . . . . . . . . . . . . . 386.2 Contribution to practice . . . . . . . . . . . . . . . . . . . . . . . . . . . 386.3 Further research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

7 Conclusion 40

Reference 41

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1 Introduction

For many years it was a common policy for food processing companies to produce in largebatches to keep production costs low and limit the number of set-ups (Van Donk, 2001).However, in the last decade changes to consumer behaviour and wishes have led to anincrease in packaging sizes and number of products. This increase in variety of productshas resulted in more complex management and the need to increase flexibility of facilities(Nakhla, 2006).

Currently, the food processing industry is using WIP buffers to decouple the packing andprocessing departments in order to provide this added variability. Therefore an importantarea that can influence a manufacturer’s operational efficiency is in its management ofits work in process (WIP) inventories (Wilson, 2013). WIP buffers, defined as inventoryfound anywhere after the end of the first step in a manufacturing process and beforethe final step in a manufacturing process (Conway et al., 1988), is one type of inventoryfound in manufacturing operations; the other two being raw material inventory and fin-ished goods inventory. Efforts to efficiently manage WIP inventory have been studiedextensively, by researchers such as Kim and Lee (2001), Askin and Krisht (1994) andPowell (1994). Their work has contributed to our understanding of areas such as theoptimal size of WIP buffers and the optimal location of these buffers.

However, the majority of research done in optimising WIP has focused on assembly-type operations, with little work done in the food processing industry (FPI) (Wilson,2013) Due to the low margin on food products in general, only low investment solutionsoptimising WIP are applicable in order to still get a good return on investment. Moroever,additional complexity is due to special food processing industry characteristicsl such asthe perishability of products, which require efforts to reduce lead times as much as possible(Mahalik and Nambiar, 2010) to avoid wasting product that cannot be sold as remainingshelf life expires.

Most of the facilities in the food processing industry have an unbalance,in terms of ca-pacity, between the processing and packaging department requiring WIP buffers in be-tween the processes. Dealing with these WIP buffers requires additional care in the foodindustry, due to spoilage, allergens and other food safety issues (Jackson et al., 2008).Furthermore, EU-regulations requires food hazards to be controlled and thus WIP buffersmust follow strict regulation. One way of controlling food hazards is by implementingHACCP, which is a systematic approach to identifying, assessing, and controlling hazards(Sanders, 1999) . Last, deterioration of products during the buffer time puts a restrictionbetween successive processes (Flapper et al., 2010).

A key step to controlling WIP in the food industry is to first optimise the work in process(WIP) level. Research is done in scheduling, by mostly scheduling rules are simplifiedversions of practice (Hopp and Spearman, 2011). Moreover, very complex methods arenecessary to solve the problem and usually are not understand by practitioners. Moreover,scheduling alone will not eliminate buffers when dealing with an unbalanced line problem,some buffers are always required and wanted (Conway et al., 1988).

Therefore, the second step in WIP control is to use Shop Floor Control (SFC) methods.

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In literature several methods are discussed namely: drum-buffer-rope, kanban, CONWIPand several Lean methods. However, in reviewing the literature regarding buffer manage-ment in the food industry limited sources can be found. A review of perishable bufferswas performed for the dairy industry by Wang et al. (2010). In their study they alsofound limited sources for dealing with buffers in the food industry.

WIP buffers in the food are specific due to the earlier mentioned regulations and otherrequirements. Especially due to the perishable nature of the products, that only allowsthem to spend a limited amount of time inside the manufacturing system. If the systemflow time, or lead time, exceeds certain fixed thresholds, the product has to be consideredas a defect and has to be scrapped by the system (Colledani et al., 2014).

As such, the problem of scheduling and buffering of perishable products have only spo-radically been addressed for simple systems, and no appropriate method for a simplescheduling heuristic for perishability has been found in the current literature regardingunbalanced production lines. The goal of this paper is to contribute to this end. Specif-ically, to investigate scheduling of unbalanced lines with perishability and managementof buffers in the food industry.

The research question is;

“What are effective methods for reducing and controlling WIP in the food processingindustry?”

In the following research, the theoretical background is discussed in the next chapter,followed by the methodology, analysis, discussion and conclusion.

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2 Theoretical background

In the theoretical background literature regarding WIP in the FPI is discussed. First, thestrategic value of WIP is explained. Second, the food processing industry in general andthe special characteristics in relation to WIP are discussed. Next, literature regardingWIP optimisation (i.e. reduction and control) is reviewed. In this part, first, the roleof production control in relation to WIP optimisation is explored. Second, the role ofsequencing methods applied in the food industry are critical reviewed. Finally, the shopfloor control literature is discussed.

2.1 Work in process

Interest in work in process (WIP) inventory has been high as it is one of the target criteriain production logistics. Lodding et al. (2003) even describes is as of ”strategic importancefor commercial success”. In literature WIP is normally defined as; ’inventory after thefirst step in manufacturing and before the last.’ (Conway et al., 1988). Different opinionsexist regarding WIP. Methods such as Lean and theory of constraints (TOC) considerWIP to be unnecessary, wasteful and it’s a goal to fully eliminated WIP (Wilson, 2013).However, other methods consider WIP usesful, as inventory cannot be excess when it isthe right quantity of the right goods at the right place at the right time (Crandall andCrandall, 2003).

In this research the main purpose of WIP is to give each stage of a production system,some degree of independent action (Conway et al., 1988). Independent action is neededto handle uneven production rates in decoupled serial operations (Wilson, 2013). Inthese situations, WIP can be used as a method of protection between working processes(Schragenheim and Ronen, 1990). Specificially, to ensure machines in the process areneither blocked (e.g. machine must wait to dispose its finished piece before it can) orstarved (e.g. next machines is waiting for material). In both blocking and starving casesa continuous processing is prevented, causing loss of production.

By studying WIP inventory it is useful to apply Little’s Law:

L = λ W,

where L is the expected number of units in the system, λ the average arrival rate of itemsto the system, W the expected time an item spends in the system (Little, 1961). Little’slaw implies that for fixed throughput, reducing WIP and reducing cycle time are directlylinked. Therefore, the measures to increase the efficiency of WIP are the same as thoseone would use to reduce cycle times.

Hopp and Spearman (2011) refined Little’s Law in terms of WIP, cycle time and through-put:

Throughput (TH) = WIP/Cycle Time (CT),

where throughput is the average output of a production process per unit time, WIP theinventory between the start and end points of a product routing, Cycle Time the time

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that the part spends as WIP.

Reducing WIP is therefore directly related to reducing throughput. Moreover, decisionsrelating to the optimal size and optimal placement of buffers are critical.

The issue of optimal WIP size mainly focuses on not carrying excessive amounts of WIPinventory. Tsourveloudis et al. (2000) specifies four reasons for maintaining low WIPlevels:

• WIP inventories tie up capital which create no profit for the company;

• High WIP inventories increase cycle times and reducing customer responsiveness;

• High WIP inventories occupy more warehouse space and increase the need for ma-terial handling equipment;

• WIP inventory increase risk of loss due to spoilage and obsolescence.

The majority of research done in optimising WIP has focused on assembly-type opera-tions, with little work done in process-type industries, such as the food industry (Wilson,2013). A discussion regarding the special characteristics of the food processing industryand its consequence for handling WIP is discussed in the next section.

2.2 Food processing industry

The food sector is based on a very diverse group of products with different degreesof perishability, varied manufacturing lead times, and demand in different amounts atdifferent frequencies (Dora et al., 2015). Despite the diverse nature of this industry asa whole, the huge variation in quality of raw materials and their highly unpredictablesupply as well as volatile customer demands make the manufacturing sector quite unique.In the table 1 the unique characteristics of the food processing industry are describedbased on literature (Wezel et al., 2006; Wilson, 2013; Dora et al., 2015).

Component Characteristics of the food processing industryPlant characteristics Expensive and single-purpose capacity coupled with small product variety and high volumes

Flow shop oriented designThere are long (sequence-dependent) set-up times between different product typesPlants are batch processing and have two to six production linesProcessing and packaging are separated because of food quality assuranceSmall and single-site factories with 30 to 100 employees

Product characteristics Variability in quality of raw materials and supply due to unstable yield of farmers.In contrast with discrete manufacturing, volume or weights are used.Highly perishable which brings along product quality and safety considerations

Production process characteristics Processes have a variable yield and processing timeShort throughput time for batches (i.e. between one to eight hours)At least one of the processes deals with homogeneous productsThe processing stages are not labor intensiveProduction rate is mainly determined by capacityFood industries have a divergent product structure, especially in the packaging stageFactories that produce consumer goods can have an extensive, labor-intensive packaging phaseDue to uncertainty in pricing, quality, and supply of raw material, several recipes are available for a product

Table 1: Food processing industry (FPI) characteristics

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2.2.1 WIP in the Food Processing industry

What typifies the FPI is their multiple serial production processes consisting of two mainstages: processing followed by packaging (Akkerman and van Donk, 2009). Moreover,FPI is characterised by a divergent product structure, wherein one source material ispackaged into multiple SKU’s (e.g. due to consumer wishes for multiple sizes and pack-aging forms) (Dora et al., 2015). The production and packaging stages are separated byWIP buffers, which allows source materials to be packaging on multiple packaging linesin multiple SKU’s. However, high capacity differences between the production and pack-aging process can occur. WIP is therefore used as a safety stock, to reduce the impactof long setup-times and variable yield of the processing department on the packagingdepartment (Van der vorst et al., 2007).

Food safety

An additional element in food processing industry when considering WIP is food safety.Specifically, food allergens which are considered a major health risk (Van Hengel, 2007).According to Food safety legislation and regulations EU (2002), all products requireidentification of ingredients on the food label to protect consumers with food allergies.

Therefore a food processor must ensure proper control and separation of all processes andWIP to prevent cross-contamination of products. Moreover, production facilities thatproduce and store multiple products and buffers have a high risk of cross-contamination(Akkerman et al., 2010). Risk of cross-contamination in buffers is mostly due to accidentalcontamination caused by; mix-ups, improper production sequencing and or, inadequatecleaning of processing and packaging machines.

Another key characteristic of FPI is perishablity of WIP buffers. Dependent on the typeof products, this might range from a couple of hours to multiple days. However, all WIPbuffers in the FPI have a maximum shelf-life period and must be processed before theexpiration date (Flapper et al., 2010). When the maximum shelf-life period is exceededthe stored product must be discharged as waste, due to food safety regulation. Not onlyis this a waste of valuable resource, food waste also has to be discarded properly and istherefore costly.

Storage

In the food processing industry, WIP inventory is typically in the form of buffer bins,tanks, hoppers, silos, drums and bulk bags; where the choice of buffer is determined bythe nature of the material, food hygiene requirements and the engineering considerationswhich would govern the intermediate storage and transport of the food material (Wilson,2013). A constraint of storing WIP in FPI is that a silo can only be used for a single prod-uct (e.g. due to cross contamination), whatever the quantity in the silo (Flapper et al.,2010). The silo requires cleaning after every use, in order to prevent cross contamination.

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2.3 Production Control

In production systems, control of WIP (i.e. proper placement, etc.) is important in orderto create flow in the production. Methods in the different layers of the production controlhierarchy can be useful to optimise WIP. The purpose of production control is to ensurethat production output closely conforms with demand (Nicholas, 2011). Ideally, it ensuresthat products are made in the required quantities, at the right times, with the highestquality. It should do these things for the lowest cost and enable production problems tobe easily identified and remedied. Figure 1 shows the production control framework ofHiggins et al. (1996) these elements of production control are described below.

Figure 1: Production Control framework

2.3.1 Strategy

The upper layer of the framework contains the long-term strategic planning. The basicfunction of the tools, in the upper layer, are to establish a production environment capableof meeting the plant’s overall goals (Hopp and Spearman, 2011).

As shown in figure 1 the starting point of production planning systems is forecasting. Inforecasting, marketing and demand information is used to generate the future demand,and to specify when and how much to produce of a particular product (Winters, 1960).Once a forecast of future demand is created, decision are made regarding the execution,wherein the physical capacity of a production plan must be matched with the forecasteddemand (Hopp and Spearman, 2011). These decisions regarding capacity concern, howmuch and what kind of equipment is required. Additional influencing factors for thesedecisions are the process requirements for making the various products and flexibility ofthe production facililties required.

Simultaneously with the decision of capacity, is the decision for workforce requirements,that support and execute the production. From the capacity plan and personnel plan an

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aggregate plan is generated. This aggregate plan specifies how much of each product isproduced over time, based on priorities and operating characteristics of the plan.

2.3.2 Tactical

The tactical tools take the long-range plans from the strategic level, along with informa-tion about customer orders, to generate a plan of action that will help the plant preparefor upcoming production (by procuring materials, lining up subcontractors, etc.) (Hoppand Spearman, 2011). Generally, it is at the tactical level a WIP/quota is set that limitsthe overall WIP in the process. Next, an aggregate plan is created from which a morespecific schedule with the appropriate factors included for each scheduling period can becreated.

Master Production schedule

In the MPS, the aggregated gross production demand is used in order to determinea weekly required production schedule (i.e. gross requirement). In general the MPScontains; current inventory status, the status of outstanding orders known as scheduledreceipts.

2.3.3 Execution

In the execution layer the direct control and weekly plans are discussed, such as Shop floorcontrol which regulates the real-time flow of material through the plant in accordance withthe schedule (Hopp and Spearman, 2011). Shop floor control most important objectiveis to minimise lead times and WIP, primarily by accurate control over which orders arereleased on the shop floor and how (Higgins et al., 1996).

2.4 Production control in FPI

Due to the downward price pressure by retailers and the overall low margins on foodproducts (Van Donk, 2001) the food processing industry focuses on low cost improvementsand solutions at the operational level. As discussed in the introduction, this research willtherefore focus on WIP optimisation through scheduling and WIP control via shop floorcontrol methods.

2.4.1 Sequencing and scheduling

First, WIP optimisation through scheduling and sequencing is discussed. Sequencing hasthe advantage of minimising the quantity of work in process and permits the utilisationof upstream slacks for handling urgent orders (Nakhla, 2006). Literature discusses theeffects of scheduling and sequencing on various measures of shop floor performance criteriain a given context (?). The order of sequence determined must be optimum or must atleast satisfy one or several predetermined performance criteria (Nakhla, 2006).

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In the literature, scheduling is discussed separately for both flow-shop and job-shops, dueto their different requirements and characteristics. In a flow shop, jobs are processed onmachines in a set order. Increases in the variety of products (e.g. currently more types,mixes and sizes of consumer packaging are required) has lead to the need for greaterflexibility of facilities. This result that not only flow shop designs are present in the FPIbut also job shop designs are used. In a job shop environment, the sequence depends oneach job. Each item has their own order to be processed on machines and may take adifferent path than other jobs.

Scheduling unbalanced production processes with multiple machines in literature is calledJob shop scheduling (JSSP), a classical operations research problem that has been consid-ered as a hard combinatorial optimisation problem since the 1950s (Chaudhry and Khan,2016). Furthermore, Garey and Johnson (1979) showed that in terms of computationalcomplexity, JSSP is NP-hard in the strong sense. Therefore, even for very small JSSPinstances, an optimal solution cannot be guaranteed.

In a job shop, every job may have a separate processing sequence, in the general JSSP,there is a finite set of n jobs to be processed on a finite set of m machines (Garey andJohnson, 1979). Each job comprises a set of tasks that must be performed on a differentmachine, and in specified processing times, in a given job-dependent order. A typicalobjective of this process is to minimise the total completion time required for all jobsor makespan. In recent years, several scheduling heuristics and algorithms have beendeveloped to optimise job shop scheduling (Chaudhry and Khan, 2016). However, as wasfound during the case study, most of these scheduling rules are hard to implement andunderstand by planners.

As a result, most planners cannot or will not use these advanced scheduling heuristicsor algorithms (Wezel et al., 2010) resulting in lower unoptimised scheduling and moreoverall WIP. In some cases simple sequencing rules such as Shortest Processing Time andShortest Setup times are used in the food processing industry (Nakhla, 2006) by planners.However, in complex situations just applying a simple sequencing rule is not alwayssuccesful. In this case reducing complexity, using combinatorial rules, and than applyingthese heuristics has been found to be an effective method (Fernandes and Lourenco, 2008).

2.4.2 Sequencing rules

Next, several simple scheduling are considered which can be usefull for reducing WIP inboth flow-shops and job shops. A review by Gupta and Bector (1989) andNakhla (2006)was used to find the following method.

Shortest processing time (SPT)

SPT is one of the most effective rules (Nakhla, 2006). With SPT the jobs are prioritisedbased on the length of the processing time starting with the shortest job (Gupta andBector, 1989). This rule permits the average production time, the quantity of work inprocess, the average waiting time and the average delay of orders to be minimised.

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Shortest setup time (SST)

When setup times are significant, it is desirable to batch together jobs from the samefamily in such a way that deadlines are met (Woodruff and Spearman, 1992) and setuptime minised. This will reduce the time spent on setups which increases the capacity andoverall throughput time. In the food processing industry long-setup times are relevant,and by applying SST, jobs will finish earlier and therefore WIP will can be decreased.

Shortest weighted processing time (SWPT)

SWPT or shortest weighted processing time is an extension to the SPT with an additionalweight factor included. The jobs are prioritised based on the processing times multipliedby an additional weight factor.

Lot splitting

Russell and Fry (1997) found that splitting process batches into smaller transfer batchesnearly always improved shop performance criteria. Lot splitting means that the batchis not produced in one processing batch, but can be separated. Small jobs clear outmore quickly than large jobs, improve performance with regard to average cycle time andmachine utilisation (Hopp and Spearman, 2011). However, small batches result in lostcapacity due to an increased number of setups.

Release list

The job releasing function controls which jobs are allowed to reach the shop floor as wellas how many jobs are on the floor. The releasing function, then, controls the level ofWIP inventory (?). By proper control of WIP the throughput can be decreased whichresult in lower WIP in the system.

Combination of rules

The combination of certain rules with a waiting time under a certain threshold is usedto avoid excessive delays in long operations (Nakhla, 2006).

2.5 Shop Floor Control

After scheduling has resulted in an optimal production plan, which balances changeoversand buffers, Shop Floor Control (SFC) systems help to organise buffers. Burbidge (1990)defines SFC as ”the function of management which plans, directs and controls the ma-terial supply and processing activities in an enterprise”. The most important activity isordering. Ordering is concerned with regulating the supply of both manufactured partsand bought items, in order to meet the production programme. The main contributionof a SFC-method is to coordinate the materials and information flow onto the shop floor(Fernandes and Godinho Filho, 2011).

A well-designed SFC module both controls the flow of material through the plant andmakes the rest of the production planning system easier to design and manage (Hopp andSpearman, 2011). Despite its logical importance in a production control hierarchy, SFCis frequently given little attention in practice. In part, this is because it is perceived, too

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narrowly, as purely material flow control. No scheduling system can anticipate randomdisruptions, but the SFC module must accommodate them anyway. Next, the range offunctions of shop floor control are given.

Range of functions

Hopp and Spearman (2011) discuss the range of function of a shop floor control method.Figure 2 illustrates the range of functions one can incorporate into the SFC module: ma-terial flow control, WIP tracking, status monitoring, throughput management, capacityfeedback, quality control, and work forecasting. The functions are discussed below.

Material flow control

At the center of these functions is material flow control (MFC), without which SFC wouldnot be shop floor control. Hopp and Spearman (2011) defines material flow control as”the mechanism by which to decide which jobs to release into the factory, which partsto work on at the individual workstations, and what material to move to and betweenworkstations”.

Figure 2: Range of functions

WIP tracking

Several functions deal with what is happening in the plant in real time. WIP-trackinginvolves identifying the current location of parts in the line (Hopp and Spearman, 2011).Traceability is an essential subsystem of quality management which is an important factorof the food industry (Moe, 1998). Moe (1998) defines traceability as ”the ability to tracka product batch and its history through the whole, or part, of a production chain fromharvest through transport, storage, processing, distribution and sales or internally in oneof the steps in the chain for example the production step”. A shop floor control methodfocuses on the internal traceability of products.

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Status monitoring

Besides the WIP positions other parameters need to be monitored. Status monitoringrefers to surveillance parameters such as machine status or staffing situation (Hopp andSpearman, 2011). Without these the material can not flow through the system.

Throughput management

Throughput management measures the output of the line and compares it with the setquota (Hopp and Spearman, 2011). An example of a specific mechanism for monitoringthe system is statistical throughput control (STC). STC tracks progress toward makingthe periodic production quota (Hopp and Roof, 1998). The system collects informa-tion about real-time status which makes it a useful place to collect and process someinformation about future events.

Capacity feedback

A different function of the SFC module is the collection of data to update capacitymeasures (Hopp and Spearman, 2011). This capacity feedback function is important forensuring that the high-level planning modules are consistent with low-level execution.

Quality control

Different move points in a system give the opportunity for establishing quality assurance.This links the SFC-method with quality control. If the operator of a downstream work-station has the authority to refuse parts from an upstream workstation on the basis ofinadequate quality, then the SFC module must recognise this disruption of a requestedtransaction (Hopp and Spearman, 2011). As already discussed is quality control an im-portant function in the food processing industry.

Work forecasting

When work is forecasted it is possible to specify when and how much to produce of aparticular product (Winters, 1960). A function of SFC is managen the material supplyand processing activities in a company (Burbidge, 1990).

SFC Methods

”Effective production control systems are those that produce the right parts, at the righttime, at a competitive cost. In literature some successful production planning and controlsystems are discussed.

Fernandes and Godinho Filho (2011) divided shop floor control methods in four classes:order-controlled systems, stock level-controlled systems, flow-scheduled systems, and hy-brid systems. The characteristics of the systems are discussed below:

1. Order-controlled systems: There is no stock of final items, once production is carriedout according to customers’ specifications.

2. Stock level-controlled systems: The decision about the release of an order is basedonly on the stock level, which pulls the production.

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3. Flow-scheduled systems: The release of an order is based on a centralised schedul-ing drawn up by the planning department. This centralised schedule pushes theproduction.

4. Hybrid systems: These have characteristics of stock level-controlled systems andflow-scheduled systems.

2.6 Lean

Next to sequencing and SPC-methods, Lean practices in combination with visual manage-ment can be used to increase efficiency and reduce costs of production in the food sector(Mahalik and Nambiar, 2010) (Goncharuk, 2009). Lean manufacturing is a system thatutilises less inputs of materials, hours and creates the same outputs while contributingmore value to customers (Womack et al., 1990). Lean practices can be used to increaseefficiency and reduce cost, however, only a limited number of studies have focused on theadoption of lean principles for buffers in the food sector (Dora et al., 2015). Some basictools will work without adaption such as; short interval control (SIC) which look at ifproduction plans are met or statistical process charts (SPC) that measure the variabilityin the process. However, other tools have not been discussed in literature, such as visualmanagement in the form of 5s, visual aids (i.e. process charts, graphical representation,colour coding, symbols) and poka-yoke. A key driver of these techniques is that everyperson involved must be able to see and fully understand the different aspects of theprocess and its status at any time through visual aids (Parry and Turner, 2006)

2.6.1 5S

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One of the most common used visual control tool is 5S (Parry and Turner, 2006). 5Sconsist of five different elements that starts with the letter ‘S’ in the Japanese language(Randhawa and Ahuja, 2017) and that are repeatedly performed and controlled to sim-plify and organise the workplace or buffer zones.

1. Seiri – sort, clearly distinguish what is needed and what is not needed;

2. Seiton – simplify, organise systems logically to make it easier for others to find, useand return tools to the original position;

3. Seiso – sweep, keep things clean;

4. Seiketsu – standardize, maintain and improve the first 3Ss;

5. Shitsuke – self-discipline, correct procedures as habit; think about how they can beimproved.

5S in manufacturing ensures that the buffers are located neatly on a well-labelled location(Parry and Turner, 2006) . It could be applied in the food industry to combat cross-contamination and create order in the buffer zones. Further, applying 5S to the buffer

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zones make them easier to maintain from a hygiene point of view (Dudbridge, 2011).Commonly food clutter (which 5S sorts) in the food production/buffer areas are;

• Last week’s production plans

• Production pens

• Machine parts

• Scrapers or other hand tools

• Raw materials for a new product trial

• Spare tickets/labels

• Redundant packaging

Applying 5S with a continuous improvement plan for buffers in the food industry reducesthe chance of cross-contamination and organises the workplace. A more generalised ap-proach on the effectiveness of this method has not yet been researched and is consideredin this research.

2.6.2 Other visual aids

Besides 5S the lean manufacturing toolsets includes visual tools that form an importantpart of the communication process which drives a factory. Examples of visual tools are:process flow charts, value stream mapping (VSM), Ishikawa diagrams, Andon boards(i.e. illuminated overhead displays providing information about the current status ofproduction and emerging problems) (Parry and Turner, 2006). However, most of thesetools are not directly useful for buffer management.

A tool that is useful is poka-yoke, which is Japanese for “Mistake-proofing” and in essenceis used to design a process so that mistakes are either impossible or are easily detectedand corrected. It makes extensive use of colour coding and methods to ensure there isonly one way of doing something (Dudbridge, 2011). For example, by making cleaningequipment fixtures a certain size so they cannot be put in the wrong place in a productionfacility. After reviewing the literature, little is known about effective ways of applyingpoka-yoke for buffer management in the food industry. However, due to its usefulness tocorrect or prevent errors it will be addressed by this research.

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3 Methodology

In the introduction a research question was proposed, in the following chapter the method-ology for answering this questions is described. First, the research questions and sub-questions are re-stated and discussed. Next, a description of methods to identify new WIPreduction methods is discussed. Wherein; the data collection via a case study and thedata analysis are discussed. Followed by a short discussion upon validity and reliabilityof the current methodology.

3.1 Research questions

The research question is; “What are effective methods for reducing and controlling WIPin the food processing industry?” In order to answer the research question multiple sub-questions are formulated to support the research question.

RQ: What are effective methods for reducing and controlling WIP in the food processingindustry?

In the research questions two main topics are discussed, reducing WIP and controllingWIP in the food processing industry. Therefore, several sub-questions arise;

SQ1: What are effective methods to reduce WIP in the food processing industry?

SQ2: What are effective methods to control WIP in the food processing industry?

3.2 Selection of methods.

The theoretical background already discussed some of the most important methods usedto reduce WIP, such as planning, scheduling and scheduling related methods. In order todetermine which methods are effective multiple characteristics of the FPI are discussedwhich were found in literature and from a case study company.

Next, a literature review is performed for methods applicable to reduce WIP in the foodprocessing industry (FPI). Herein; backwards and forward search is used on key articlesof (Gupta et al., 1999; Dora et al., 2015; Wilson, 2013; Johnson, 1954) to find applicablemethods.

All appropriate scheduling methods are filtered and rated on key characteristics of theFPI. An overview is created which helps select the capable methods. An analysis of theselected scheduling rules is performed using a case company data.

A similar procedures is performed for the methods that control WIP on the shop floorof food processing industry companies. First, a list of SFC-methods are collected fromliterature. Again, the list of SFC-methods is rated on key characteristics of FPI andapplicable methods are selected. Second, these filtered SFC-methods are validated at thecase company, which is discussed later.

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3.3 Case study

A case study is performed in order to gain knowledge of the food processing industry, findappropriate solutions which can be generalised. Moreover, the experts in this companycan provide with valuable feedback and validation of explored methods. The case com-pany involved produces peanuts and nuts for the European, Australian and Philippinemarkets. Duyvis was the first peanut factory who came up with special peanuts and nutslike the ‘Borrelnootjes R©’, ‘Tijgernootjes R©, and Oven Roasted Peanut and Nuts. With125 employees Duyvis produces five days a week in three shifts to supply to its customers.

Duyvis has six processing lines who sent their output to multiple packaging lines. Bothdepartments are separated by intermediate WIP buffers. From a processing line a productcan be packed on different packaging lines and create multiple SKU’s, The current processresult in a lot of variability in the material flow and in initial interview the managersindicate that WIP buffers have become uncontrolled an a food hazard. The case studycompany shows typical problems for a job-shop and is in need for better WIP controlmethods.

3.4 Data collection and data analysis

Figure 3 gives an overview of the methodology. Firstly, an overview was given of theexisting literature of work in process with definitions, the current states of WIP literatureand the function of WIP. Secondly, literature of the characteristics of the food processingindustry in combination with WIP was explored. Next, literature of the optimisationof WIP is explored. This exist of exploring literature of sequencing and literature ofshop floor control. Both are explored in general but also applied in a food processingenvironment.

Using scheduling data the company provided, a simulation of the current WIP build-up iscreated and several effective JSSP which are easily implementable by planners are tested.

Moreover, a the effective shop floor control methods, which control WIP, at the casestudy company are discussed. First an analysis of the current shop floor control methodsis performed and usuable methods are filtered out. Next a validation is performed,discussed later.

At the company multiple in-depth interviews are conducted with multiple stakeholdersin the handling of the WIP buffer. The functions of these people are listed below:

• FLM planning

• Planner

• Lean manager

• Processing specialist

• Operator Coated 1

• Operator Coated 2

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Figure 3: Overview Methodology

• Operator Peanutline 1

• Bin distributor Coated 1

• Bin distributor Peanutline 1

• Bin distributor Peanutline 2

• FLM operations

• TE processing department

• Food Safety specialist

• Quality specialist

All interviews are recorded, however, due to privacy reasons have not been included in thisresearch. Last, observation sessions where conducted to gather data about the currentWIP buffer control at the shop floor. Finding the problems and searching for effectivesolution.

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3.5 Validation of effectiveness

One of the key deliverables of this research is the effectiveness of the shop floor controland scheduling methods described and discussed. Therefore, a validation at the case-study company is performed along the lines of key FPI characteristics and requirements.A validation session is held with the interviewees earlier described and already performedmethods are further discussed on their effectiveness. Operational scenarios for each shopfloor control methods are provided which are discussed and rated on several importantfood processing characteristics. These interviews are recorded and the important ratedelements discussed in the validation.

3.6 Validity and reliability

A case study is performed in this research which has some validity and reliability problemswhich have to be addressed. Because this reports is used as knowledge exploration andvalidation is tested in general and not specifically for the company some generalisabilitycan be provided. However, for future research a multiple case study would be bettersuited to investigate this problem.

Appropriate investigation techniques and testing of the scheduling heuristics and methodsis conducted in order to increase the validity.

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4 Analysis

In the analysis chapter the methods for controlling and optimisation of WIP in the Foodprocessing industry are discussed. First, the scheduling methods and rules to reduceWIP are analysed at the case-company. Next, the shop floor control methods which helpmanage and control WIP are analysed in the case study environment. Last, the Leantools implemented at the case company are analysed.

4.1 Scheduling at the case-company

The case-study companies factory has six processing lines which send their output tomultiple packaging processes. In figure 4 an overview of the material flow in the factoryis given, left the processing lines are displayed and right the packaging lines. Eachprocessing line sends their output to a buffer. From this buffer the product can beprocessed on multiple packaging lines (for multiple SKU’s). Due to the non-fixed orderof machines for a job, this process can be characterised as a job-shop environment.

The processing department is located on the first floor, whereas the packaging depart-ment is located below on the ground floor. As already mentioned, the processes are notdirectly connected (i.e. via a direct feeding line) but have intermediate storage. Thisintermediate storage area is located at the processing department, where materials arestored in storage-bins and cars. Currently, the different processing capacity of both de-partments causes continues buffer build-up during the week. Consequently, difficulties incontrolling these buffers require strict policies and additional effort.

The Lean manager and manager of the planning department stress that, low investmentsare preferable in the food industry. Due to the low margin on the products it is hard toget a good return on investment with high investments. Continuous improvements andlow cost solutions using current resourcese is therefore preferred.

4.1.1 Tactical decision: MPS

Currently, the MPS (Master Production Schedule) is determined yearly, for a four weeklycycle. In the MPS several product families are created based on product type, allergensand changeover activities (i.e. less changeover times). Moreover, for each productionfamily the weekly production quantities are determined using forecast data, facility pro-cessing capacity and the work-force available. Resulting in an MPS, which for Duvyis isan approximation of the production required for each product in each week. This processis shown in figure 5.

4.1.2 Production schedule

Each week, the final SKU production demand is determined by the Supply-Chain depart-ment. Using the latest forecast, inventory level information and safety stock requirements

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Figure 4: Material flow

Figure 5: Current situation - MPS Duvyis

for all SKU’s. Only the products determined by the MPS can be planned in that week.

Next, the planner applies a forward scheduling approach to create the production schedulefor each week. No additional support scheduling rules are used, however, the planner willlook at the allergen changeover matrix (optimised changeover) to reduce the total setuptime.

First, for all SKU’s the source material are grouped and scheduled at the processingdepartment. By grouping the source material, the shortest setup time can be appliedwhich result in reduced changeovers at the processing department. In general the plannerwill follow the optimal allergen changeover matrix, which has been devised during theMPS stage. Second, the packaging department is planned, wherein the planner looks at

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starting times of products and the total processing times.

Every Thursday the production schedule is discussed with the operations department,adding maintenance or other special activities to the schedule. After finalising the weeklyproduction schedule, the ownership is transferred to operations, who is responsible for theexecution of the production plan. In case of interruptions (due to unexpected breakdownsor maintenance) the operation department will also make decisions regarding changes tothe schedule. The planning department will only function as support during this process.

Figure 6: Current situation - Planning Duvyis

4.1.3 Scheduling decisions

As previously mentioned, a planner will apply forward scheduling and tries to schedule allthe jobs of the processing department in the first three days of the week. In an interviewwith the manager of the planning department he said;

”this decision was made when the MPS was first established, due to labour cost require-ments and the gained flexibility for the end of the week”

Currently, the intermediate storage is used to create more flexibility and to take care thatthe processing department finishes early in the week. This gained flexibility is needed forany unforeseen technical problems and allows more freedom in the work-force planning.Furthermore, labour cost can be reduced because at the end of the week no operatorsare needed. However, since the processing department has a higher average output theintermediate storage slowly fills up during the week.

Currently, the case-company does not consider this buffer build-up in their productionschedule, as flexibility and labour cost were valued higher when the MPS was established.Recently, the company has discovered that this buffer causes several problems. Becausethere is a lot of intermediate storage at the shop floor operators lose overview which resultin inefficient working and making mistakes.

Figure 7 shows the WIP buffer flow at the shop floor during week 41, with the currentway of scheduling. It provides information of the WIP build-up, the cumulative WIP ofall lines, and the total bins stored in the buffer. It can be seen that buffer builds up in thebeginning of the week and slowly decreases as the week progresses. The total bins storedis higher than the cumulative WIP because bins cannot be shared by multiple sourcematerials due to allergens. A bin approximatly contains 200 KG of product. Figure 8and figure 9 give more insight in where the build-up comes from. Figure 8 shows thatindeed most of the products are produced in the first half of the week. The build-upin the first 20 hours is around 8000 KG but figure 9 shows that there is only 4500 KGprocessed.

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Figure 7: WIP - current situation

Figure 8: WIP produced - current situation

4.2 Scheduling in the FPI

In the following part sequencing rules are analysed on their effectiveness for WIP opti-misation in the food processing industry. Firstly, the sequencing rules are analysed bylooking at a direct one to one machine situation (i.e. complexity of the job shop schedul-ing is reduced). Secondly, an overall optimisation method of the entire production facility(i.e. a job-shop) is discussed

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Figure 9: WIP processed - current situation

4.2.1 Applying sequencing rules

As discussed in the theoretical background, most sequencing rules are not applicable incomplex situations (i.e. job shop). Therefore, complexity needs to be reduced (Hopp andSpearman, 2011), for the case-company, MPS data and production quanities of week 40and 41 are used. First, for both weeks a one to one machine situation (i.e. flow-shop)is used as a simplification. Next, several sequencing rules are applied on this one toone machine situation namely: shortest processing time (SPT), Johnson’s rule, shortestweighted processing time (SWPT), shortest setup time (SST), SPT with a release list,SST with a release list, SPT with a release list and with lot splitting, and SST witha release list and with lot splitting. A short description of the priority rules are givenbelow:

Shortest processing time (SPT):

Jobs are prioritised based on the length of the processing time starting with the shortestjob (Gupta and Bector, 1989).

Johnson’s rule:

Johnson (1954) developed a scheduling heuristic for the n jobs on two sequential machines,so that the total time processing time is minimised for the whole operations. The timerequired to process each job at each machine is listed in two vertical columns (Johnson,1954). Next, all time periods are scanned for the shortest processing time. When theshortest processing time is for the first machine, place the corresponding item first. Whenit is for the second machine, place the corresponding item last. Once the item is placed,cross off both times for that item. Repeat the steps until all items are placed.

Shortest weighted processing time (SWPT):

Jobs are prioritised based on the processing times multiplied by an additional weight

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factor. For WIP reduction purposes this weighted factor is calculated by dividing theprocessing time of the first machine by the processing time of the second machine. Next,the SPT procedure is applied (Gupta et al., 1999)

Shortest setup time (SST):

Jobs are prioritised based on the length of the change-over times starting with the shortestchange-over job.

SPT and SST with a release list :

A release list is added to the SPT and SST rule, jobs will arrive at the second machinewhen capacity is available at this machine (Hopp and Spearman, 2011).

SPT and SST with a release list and with lot splitting :

Lot splitting means that the batch is not produced in one processing batch, but can beseparated in, for example, two batches. Lot splitting is added to the SPT and SST rulewith a release list.

Results of the analysis of sequencing rules for week 40 and 41 are shown respectivelyin figure 10 and in figure 11. For week 40 the processing line ”BK” is producing forpackaging line 9. For week 41 the processing line ”BK” is producing for packaging line1 and 2. From these graphs it can be seen that; SPT, Johnson’s rule, the SWPT andthe SST; build up the amount of WIP during the first half of the week. The highestpoint is reached in the middle of the week and WIP is processed at the end of the week,observations at the case study also show this process. An SPT and SST with release listand with lot splitting reduce the maximum amount of WIP kg’s and bins on the floor,processing times are spread out and larger changeover are required. However, these reuleshave resulted in a lower overall buffer.

Figure 10: Buffer week 40

Table 10 and table 11 give more detailed information about the performance of thesequencing rules. For both the processing and packaging department it displays; thefinish time of production, total processing time, and changeovers in hours. Moreover,

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Figure 11: Buffer week 41

for the processing department the additional variable time of the machine is displayed.Finally, for each rule the maximum KG of buffer and the amount of bins were calculated.The tables show that the rules with the release list and with lot splitting have higheradded variable time, however, the maximum total of bins are half or even two third lower.

Processing Packaging WIPHour production

finishedTotal processing

time (hours)Changeover

(hours)Variable time

machine (hours)Hour production

finishedTotal processing

time (hours)Changeover

(hours)MaxKG

Totalamount of bins

Shortest processing time (SPT) 66,28 63,28 3 0,00 103,51 96,51 7 38415 192Johnson’s rule 66,28 63,28 3 0,00 103,51 96,51 7 38415 192Shortest Weighted Processing Time (SWPT) 64,76 61,76 4 0,00 99,16 91,66 7,5 41007 205Shortest setup time (SST) 66,28 63,28 3 0,00 102,26 96,51 5,75 40230 201SPT with release list 85,77 63,28 3 19,48 109,26 96,51 12,75 19969 100SST with release list 82,72 63,28 2 17,44 102,26 96,51 5,75 26289 131SPT with release list with lot splitting 94,81 65,33 6 23,48 109,26 96,51 12,75 14300 71SST with release list with lot splitting 91,24 59,71 6 25,53 109,26 96,51 12,75 10808 54

Table 2: Results sequencing rules week 40

Processing Packaging WIPHour production

finishedTotal processing

time (hours)Changeover

(hours)Variable time

machine (hours)Hour production

finishedTotal processing

time (hours)Changeover

(hours)MaxKG

Totalamount of bins

Shortest processing time (SPT) 44,76 41,76 3 0,00 115,29 106,29 9 46988 235Johnson’s rule 44,76 41,76 3 0,00 115,29 106,29 9 46988 235Shortest Weighted Processing Time 44,76 41,76 3 0,00 115,29 106,29 9 46988 235Shortest setup time (SST) 43,76 41,76 2 0,00 112,29 106,29 6 42936 215SPT with release list 72,13 41,76 3 27,37 115,29 106,29 9 30277 151SST with release list 96,98 41,76 2 53,21 112,29 106,29 6 26289 131SPT with release list with lot splitting 98,13 54,82 4 39,32 112,29 103,29 9 17713 89SST with release list with lot splitting 93,23 41,76 3 48,46 112,29 106,29 6 14844 74

Table 3: Results sequencing rules week 41

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4.2.2 Overall optimisation

As previously mentioned, a simplification of the overall scheduling is required to getresults for this problem. First, a local optimisation of one processing line to one pack-aging line was performed and analysed. Now, the overall optimisation of this job-shopscheduling process is performed and analysed. In these situations the tested rules can beapplied.

An important rule to optimise WIP is that just one machine of the processing departmentcan produce for one machine of the packaging department. It should not be possiblethat two machines of the processing department simultaneously produce for the samemachine of the packaging department (i.e. to keep WIP low). When a processing linefinishes producing for a packaging line it can start producing for another packaging line.However,only if the packaging line can start processing the output of the processing lineimmediately.

A simplified one to one machine situations (i.e. flow-shop) can be created from thecase-situation (job-shop) using the following steps:

1. Create a table with the total processing times of the departments (int this case forthe packaging and processing department).

2. Ensure the total sum of the processing times of each production line is below themaximum total processing hours. (Example: when there is 5 days of production5x24=120 hours).

3. First, create blocks for the production line who’s output gives input to one machine

4. Second, identify the production line with the most total processing line, plan thelargest processing time first.

5. Repeat step 4 and 5 until all blocks are assigned.

6. Apply the sequencing rule separately for each block.

Figure 12 shows a block diagram where the steps are applied on the case company data.Dark colours represent the time the processing line is producing for that batch. Lightercolours represent the time the packaging line are still producing.

Figure 12: Block diagram week 41

Figure 13, figure 14, and figure 15 show the results when applying SPT and capacitylevelling to the blocks showed in figure 12. When applying these rules the WIP level ishalf of the WIP level compared to scheduling in the current way.

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4.2.3 Additional optimisation

In literature, simple visual tools have not been discussed, however it was found duringthis study that WIP can be further decreased with some simple adjustments.

Line balancing of the overall facility output on both production and processing can beperformed using the graphs. For example, simply delaying some production jobs in theweek and levelling the production and packging lines results in the production of 6000KG of products per hour and the processing of 6000 KG of products per hour as well.Applying capacity levelling balances WIP during the week and decreases the maximumbuffer output for week 41 to 150 bins.

Figure 13: WIP - Line balancing

Figure 14: WIP produced - Line balancing

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Figure 15: WIP processed - Line balancing

4.3 Effectiveness of Shop Floor Control measures in the foodindustry

After limiting and optimising the WIP through scheduling, the left-over WIP still needsto be controlled on the shop-floor. In this section, first, the current way of controlling thebuffer is discussed. Second, an analysis of effective shop floor control methods suitablefor the food processing industry and WIP control is discussed.

4.3.1 Material handling at the shop floor

In the case-company decisions regarding the location and storage of the buffer are madeat the shop floor, the process is shown in figure 16. The operator gives the bin distributorinstructions about, for example, the location of the buffer. Next, it is the job of the bindistributor to fill and transport the storage bins.

There are no rules concerning the intermediate storage. The case company tried toorganise the shop floor by applying 5S. On the floors lines indicate the location of abuffer. The processing operators indicated in interviews that they try to locate the bufferin an assigned buffer location and close to the pouring hole of the packaging line whereit is intended for. However, this is not always possible due to the crowdiness of thestorage lots and many bins located close to the packaging line. Currently the processingcan be described as unorganised, and ad-hoc rules wherein operators try to manage/findplacement of the storage bins.

Operators indicate they lack overview of the shop floor, the contents of the storage binsand their storage location. Resulting in longer search times (and annoyance of the oper-ator) for required products and more mistakes. Figure 17 shows a map of the shop floor,black outlined squares represent the buffer location, yellow lines are the footpaths, and

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the green squares represent the pouring holes of the packaging line. The map is createdbased on observations.

Figure 16: Current situation - Buffer process Duyvis

Figure 17: Map buffer locations

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4.3.2 Classification of SFC-methods

In order to find shop floor control methods that can be used in the food industry, a two-stage filtering process is performed. First, the shop floor control methods are rated onthree basic characteristics namely: if it is suitable for a flow shop, if it helps to reduce WIPon the shop floor, and if it does not require high investments. The three characteristicsare discussed below.

Flow shop

A flow shop is a repetitive and continuous operation producing similar or identical itemsin high volumes (usually found in the FPI). Materials move through them somewhatsmoothly and with few interruptions (Nicholas, 2011). The shop floor control systemmust take into account two separate processes in serial, with different capacities.

Reduction of WIP

The method needs to intent to control or reduce the total work in process. It needs togive overview of the work in process in the system as well to control that, no jobs arereleased when the capacity can not handle the flow. When the jobs can not be handledthe consequence can be that the job is not processed on time.

Low investment

Last, an initial requirement of this research was to find the methods of continuous im-provement and control that require minimal investment (since SME’s do not have muchinvestment capabilities). Moreover, the FPI deals with low margin on their products andthe return on investment of most high cost SFC-methods is simply to high.

Each method requires to score a + on all three characteristics to be selected for the secondfilter. Methods scoring three pluses are categorised green, others are categorised in red.Results of the first filtering are shown in the first half of figure 18.

Figure 18: Shop floor control methods

For the second filtering the characteristics changeovers, perishability, variability and stor-age constraints are taken into account. The characteristics are discussed below:

Changeovers

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Regardless of batch size, whenever a machine must produce a different product, machinesand fixtures at each station must be changed over (Nicholas, 2011). Changeovers in thefood industry are often sequence dependent and are critical due to the food-safety issues(Yash Dave and Nagendra Sohani, 2012). EU-regulations require control of buffers toprevent food hazards (Sanders, 1999). In production facilities where multiple productsare produced in the same location, there is a high risk of cross-contamination. Cross-contamination means that allergenic proteins from one product are carried into the nextproduct (Jackson et al., 2008). This makes it important that allergens and other un-wanted materials are cleaned and separated. In the food industry, cleaning times (dueto allergens), and start-up losses result in long set-up times, therefore, long runs arepreferable from a production perspective (Wezel et al., 2006). An effective SFC-methodtherefore should help control and optimise for changeovers and longer production runs.

Perishability

In the food processing industry raw material, semi-manufactured products, and end prod-ucts are perishable (Van Donk, 2001). There is a time constraint for perishable buffers,which means that the products can only be stored for a limited period (Flapper et al.,2010). When this period is exceeded the stored product will be discharged as waste, dueto food safety regulation. It is important that a SPC-method can ensure that the buffersare processed before the maximum period is reached. Due to quality, environmentalrequirements and product responsibility there is a necessity for traceability of work inprocess (Van der vorst et al., 2007). As already discussed, buffers need to consider foodallergens which are considered a major health risk (Van Hengel, 2007). A SPC-methodneeds the ability to register and provide information of WIP to be sure the time periodis not exceeded.

Variability

Two types of variability can be distinguished, namely; variable yield and variable pro-cessing times.

Variable yield:

Variable yield is due to waste during the process which has to be re-worked or scrapped.Moreover, this results in additional production quantities being planned to end up withenough final product. A shop floor control method must be capable of dealing withvariable yields in their WIP systems.

Variable processing times:

Especially in the packaging phase, the food industries have a divergent product structure(Van Donk, 2001). From one source product multiple SKU’s are produced with differentcharacteristics and processing times (i.e. packaging size, etc.). The SFC-method musttake into account differences in production capacity (between multiple SKU’s), packagingon different production lines, and between the processing and packaging department.

Storage

Storage buffer capacity is restricted, when material, intermediates or finished productscan only be kept in special tanks or containers (Van der vorst et al., 2007). Most buffers

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need to be stored near the work floor/process and are constrained by limited storagespace and storage bins. In the food industry, when the next machine cannot processthe incoming capacity, additional products are stored in specialised silos or food storagecrates. Storing in silos is common, but unfavourable, since a silo can only be used fora single product (e.g. due to cross-contamination), whatever the quantity in the silo(Flapper et al., 2010). Subsequently, the silo has to be emptied, cleaned and checkedbefore re-use. Storage crates are used for other temporary smaller size buffers, howeverproperly organising these buffers is a challenge. The SFC-method need to take intoaccount the limited storage space and must be suitable for multiple storage types.

Validation

Similar to the first filtering round each of the SFC methods is scored using + or - anda minimal of three pluses are set as the limit for validation. In the next chapter thesemethods are validated with case-company representatives and rated for their effectiveness.

4.3.3 Lean

In the case company an additional Lean tool is used namely ”QCDM”. QCDM stands forQuality, Cost, Delivery, and Moral. Every one hour, four hours, twenty-four hours, week,and period a ”QCDM” meeting is held. In every meeting different people of differentlayers of the organisation are present. The aim of ”QCDM” is continuous improving. Itstarts at the shop floor. Every operator is responsible for a zone. For every zone a KPI isset on Quality, Cost, Delivery, and Moral. An indicator turns red when a KPI is not met.Every hour the department manager checks the boards and asks the operator to explainthe red indicators. What is the problem? What did you already do to solve the problem?Can you solve the problem? When do you expect the problem is solved? When theoperator cannot solve the problem the department manager discuss the problems withthe other department manager and the team manager in the four hour meetings. All thedepartments have their own KPI’s. In the twenty-four hour meeting the managers of allthe departments discuss the red KPI’s. Also the managers mention what the cause is ofthe problem and when the problem is solved. When the root cause is unknown 5why’sare used to find the root cause. In the weekly meeting the management team discussesproblems that cannot be solved in the twenty-four hour meeting. In the weekly meetingprojects are set-up to improve the processes on the items that came from the twenty-fourhour meeting. Also Gemba-walks are done to spot if everything is still on standard.Lastly, the period meeting discusses the problems that cannot be solved in the weeklymeeting.

The Lean manager mentioned that the buffer problem is never mentioned in the ”QCDM”meetings. This is interesting because the operators are irritated by the lack of overview.”QCDM” is an interesting tool to sent feedback and improve processes. The Lean man-ager thinks that ”QCDM” is not used to solve the issue because there are no rules orKPI’s who tell if something is wrong or right. When applying a shop floor control methodand KPI’s the buffer process can be reviewed using ”QCDM”, which result in continuousimprovement of the buffer process.

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5 Validation

In this chapter the shop floor control methods drum-buffer-rope, hybrid CONWIP, hybridtwo-boundary control, and minimal-blocking are validated. During the validation the fourmethods are discussed with the Lean manager, manager of the planning department, anda co-operator of the Lean department who also has experience with operations.

5.1 Drum-buffer-rope

The first SFC method is drum-buffer-rope. The method is based on the Theory of Con-straints (TOC) and focuses on the systems constraint (Goldratt and Cox, 2004). Threemajor components of DBR are the drum, the buffer, and the rope. Lower capacity sta-tion, which governs the throughput rate of the entire manufacturing line, are known asthe ”drum”. The drum has to include a detailed schedule of the constraint in order toensure the exploitation of the constraint. A ”buffer” is protection time (Schragenheimand Ronen, 1990) and is placed before the constraint. The purpose of this buffer is toprotect the drum against unexpected fluctuations in the flow of materials. Last, the”rope” is a material release mechanism to force all parts of the system to work up to thepace dictated by the drum and no more (Spearman et al., 1990).

DBR enables better scheduling and decision making on the shop floor (Schragenheimand Ronen, 1990). It only releases jobs when the bottleneck can handle the capacity.This prevents excessive WIP build-up in the process by limiting the input for the thebottleneck process. DBR is tested in job shop environments (Spearman et al., 1990)which makes it suitable for processes with variability.

A basic version of drum-buffer-rope is practised at the case company. Currently, the drumand the buffer are present. Only the rope is not present. According to the Lean managerthere is no signal that the intermediate storage is too little or too high. Applying therope will give more insights.

Changeovers can be taken into account when scheduling the constraint. But in generalno changes to either cleaning, set-up requirements or start-up /stop losses are taken intoaccount.

As mentioned by the manager of the planning department, the benefit with this systemis knowing the maximum amount of bins on the production floor. The problem with thissystem is that there is no sequence and direct location tracking of the buffer on the shopfloor. This is a requirement when taking perishability into account. When placing a binin the buffer it is important that the products does not exceed the maximum time.

In conclusion, DBR is applicable and already used in the food processing industry. Themethods can be used to help control the work in process of the system. For the casecompany it is interesting to implement the ”rope” mechanisme. The rope will signal ifthe intermediate storage is too little or too high.

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5.2 Hybrid CONWIP

With hybrid CONWIP the total work in process is limited by the number of cards. Anavailable card has to be present to authorise a job entering the production line (Spearmanet al., 1990). The card is attached to the job that is being routed through workstations.When the processing of the job is completed, the card is removed and made availableto authorise another job to enter the line. The orders that need to be processed in theproduction line come from a backlog list (Fernandes and Godinho Filho, 2011). Thebacklog list dictates what goes to the line, and the card decides when.

According to the manager of the planning department, the system could be applied inthe food production industry when the plant has a flow shop design. In case of Duyvisthe system is difficult due to the job shop design of the factory. This causes variabilityin the material flow.

Furthermore, there is a chance of a lot of start and stop moments which result in waste.High utilisation is preferable and CONWIP risks that the machines stand still becauseno authorisation card is available. This will influence the utilisation rate. There is also arisk that the total amount of jobs for that week cannot be produced when the processingline is not able to start before the packaging line is finished. Because there is a maximumamount of WIP in the system the throughput time will decrease, which is positive whentaking into account perishability. The co-worker of the Lean department added that itis important that the bins are processed based on the First in First out (FIFO) priorityrule. This will secure that the product is not to long on the shop floor and this willenhance the quality of the product.

Last, changeovers can be considered when applying hybrid CONWIP. The backlog listdetermines the sequence of the jobs. Changeovers can be considered in the backlogbecause the length of the changeover is sequence dependent. This means that this methodcan consider the optimal changeover times.

In conclusion, the hybrid CONWIP system could be applicable in the food processingindustry when the plant has a flow shop design. When the factory has more job shopcharacteristics the hybrid CONWIP method will influence the utilisation rate.

5.3 Hybrid two-boundary control system (TBC)

The hybrid two-boundary control system combines kanban and CONWIP (Bonvik et al.,1997). The CONWIP card authorise a job entering the production line (Spearman et al.,1990). Inventory between each of the stages is controlled by kanban cards. The kanbancontains information such as the kanban type, product name and number, the locationof the buffer and the destination of the buffer (Gupta et al., 1999). In a kanban system,each card is used to signal production of a specific part (Spearman et al., 1990). In thehybrid TBC the last stage has no kanban control. The first production stage requires twoauthorisation cards: a kanban card from the second stage and a CONWIP card from thelast stage. The CONWIP card has to do with the upper limit of total WIP allowed in the

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system. The authorisation cards are based on scheduling (Fernandes and Godinho Filho,2011).

The reasoning for the hybrid TBC is partly the same as for the CONWIP system. Thesystem could be applied in the FPI when there is a flow shop design and not a job shopdesign. Moreover, the it can be implemented when the utilisation rate is not important.The difference is that kanban is not suitable for environments with a lot of variabilityand long changeover times. Partly the changeover time can be reduced because in theFPI changeover times are mostly sequence dependent. The sequence can be determinedin the backlog list.

Likewise the changeovers, perishability works the same for the TBC system as for theCONWIP system. To be applicable for the FPI the products already in the system needsto be processed based on the FIFO priority rule to prevent that the product is to long atthe shop floor.

To conclude, the hybrid two-boundary control system is not applicable to the food pro-cessing industry. Especially the kanban part needs ideal conditions to work effective.Kanban does not work well with a lot of variability and long changeover times which isthe case in the FPI.

5.4 Minimal-blocking system

The minimal-blocking system has a lot in common with the kanban system. The differencewith the systems discussed before is: ”if the machine upstream finishes its operationbefore the machine downstream, and the demand occurs at the downstream machinein the meantime, the upstream machine can start a new operation” (So et al., 1988).Therefore, as a machine can start its operation as a result of either a requisition from thedownstream machine or a schedule.

The minimal-blocking system solves the problem of the hybrid CONWIP system andthe two-boundary control system. Because the upstream machine can already start anew operation when the downstream machine is still producing the utilisation rate ishigher. This makes the system not only applicable to the food processing industry, butalso interesting for the case company.

Changeovers can be taken into account because there is a schedule involved in this system.Also in this system the changeover times can partly be reduced because the sequence ofthe jobs can be determined in the schedule.

When taking into account perishability. It is important that FIFO is applied to controlthe time the product is placed in the intermediate storage.

In conclusion, the minimal-blocking system is not only applicable to FPI but also to thecase company. Mainly because in this system the utilisation rate of the upstream machinecan still be kept high.

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5.5 Conclusion of validation

Concluding from the validation, all four methods are applicable to the food processingindustry. ALl methods are applicable in a flow-shop and can at least work in a job-shopenvironment, controlling the WIP level. For the case-company drum-buffer-rope andthe minimal-blocking system has the most potential to control the WIP level in theirproduction facility. Mainly because these methods keep the utilisation rate high, whereasthe other methods cannot guarantee a high utilisation rate.

Last, an important comment is added when applying these methods in the FPI. Whenapplying the methods in the FPI the WIP buffer needs to be prioritised based on theFIFO rule to control the time the product is placed in the intermediate storage.

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6 Discussion

In this chapter an overview is given of the contribution to literature, contribution topractice, and the limitations and suggestions for further research.

6.1 Contribution to literature

The results presented in this research show how WIP can be optimised in the food pro-cessing industry. This research shows that the FPI has different characteristics comparedto other processing industry’s. Due to these characteristics different methods need to beapplied while handling WIP.

The research extend the WIP optimisation methods used in flow-shop scheduling of per-ishable products by researching the scheduling heuristics in the food processing industry.Finding the important parameters and influencing factors for WIP reduction. Also amethod for simplification of job-shop scheduling rules have been shown, which help im-prove WIP without applying complex algorithms. Moreover, a visual technique based oncapacity balancing, which can be easily applied by planner is shown to reduce WIP inthe FPI.

Furtermore, research regarding the applicability of shop floor control methods in thefood processing industry are given and validated in a food company. In conclusion ofthe validation, the drum-buffer-rope and the minimal-blocking system are applicable inthe FPI with a job shop environment. In both methods perishability needs to be takeninto account and FIFO needs to be applied. Another important characteristic of bothmethods which make the methods suitable for the FPI is that the methods keep theutilisation of the machines high. However, more research in the general applicability.

In addition, the case company showed that ”QCDM” is a useful Lean tool to constantlyreview processes. Duyvis showed its relevance to the FPI and its contribution to control-ling the WIP buffer.

6.2 Contribution to practice

In practice, complex situations need difficult algorithms and high investments to solveproblems. Managers need to be aware that when complex environments are broken downin multiple pieces more simpler solutions can be applied. Consequently, managers need tobe aware that scheduling methods such as shortest processing time and capacity balancingare capable of reducing WIP in the FPI. Shop floor control methods such as drum-buffer-rope and minimal blocking are operational methods for controlling WIP in the FPI. Thesemethods fit in a job-shop environment where high utilisation is preferable.

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6.3 Further research

Due to the single case study this research has several limitations, generalisability is needsto be considered. Furtermore, rules and methods are tested in a job shop environmentand need to be tested in a flow shop environment to expand the research of WIP methodsapplicable in the food processing industry.

Further research study in more FPI environments is needed. The food processing industryhas different characteristics compared to other processing industy’s. In this research onlya validation of methods is performed. Methods need to be implemented to get more dataabout the performance of the methods in FPI,

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7 Conclusion

Currently, the majority of research in optimising WIP has focused on assembly-type op-erations, with little work done int the food industry. Moreover, most of these schedulingrules are not applicable by companies due to their complexity or the need for advancedsoftware. Methods for optimising and controlling work in process in the food processingindustry are presented in this research. The FPI needs to apply low investment solu-tions, due to the low margin products but also due to the complex characteristics. Thisresearched showed that by breaking down the complexity, simpler sequencing rules canbe applied to optimise WIP. Furthermore, simple visualisation can help planners controlWIP in the food processing industry.

Additional by applying shop floor control methods the food processing industry canoptimise and control WIP. This research showed that drum-buffer-rope and the minimal-blocking system are applicable for the food processing industry. However, more researchis needed regarding the implementation of these methods. An addition to these usesof these methods is to apply the FIFO priority rule to the WIP buffer to ensure theexpiration date is not exceeded.

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