Literature Review on

Group Technology and Cellular Manufacturing

By

Sandeep Bagul

Cellular Manufacturing:

Introduction:

In today’s business world, competitiveness defines an industry leader. The drive toward

maximum efficiency is constantly at the forefront of such companies’ objectives. Managers

across the country are striving to adopt lean manufacturing practices to help address worries

about their bottom line. Cellular Manufacturing is one staple of lean manufacturing.

Cellular Manufacturing is an approach that helps build a variety of products with as little waste

as possible. A cell is a group of workstations, machine tools, or equipment arranged to create a

smooth flow so families of parts can be processed progressively from one workstation to another

without waiting for a batch to be completed or requiring additional handling between operations.

Put simply, cellular manufacturing group’s together machinery and a small team of staff,

directed by a team leader, so all the work on a product or part can be accomplished in the same

cell eliminating resources that do not add value to the product.

How to incorporate cellular manufacturing?

The implementation process of shedding the traditional manufacturing processes and embracing

the drastically different cellular manufacturing techniques can be a daunting task. Management

must deal with many issues including: cell design and set up, team design and placement,

employee training, teamwork training, as well as other company functional issues. A project

team should be put together that consists of management and production employees to handle

these changes.

Cell Design and Setup:

It should be executed to facilitate the movement of the product through its production cycle and

should also be able to produce other similar products as well. The cells are arranged in a manner

that minimizes material movement and are generally set up in a “U” shaped configuration.

Team Design and Placement is a crucial part of the process. Employees must work together in

cell teams and are led by a team leader. This team leader becomes a source of support for the cell

and is oftentimes responsible for the overall quality of the product that leaves his/her cell.

Employee Training must also accompany the change to cellular manufacturing. In cellular

manufacturing workers generally operate more that one machine within a cell which requires

additional training for each employee creating a more highly skilled workforce. This cross-

training allows one employee to become proficient with his/her machines and while also creating

the ability to operating other machines within the cell when such needs arise.

Teamwork Training should generate camaraderie within each cell and stimulate group related

troubleshooting. Employees within each team are empowered to employ ideas or processes that

would allow continuous improvement within the cell, thus reducing lead times, removing waste

and improving the overall quality of the product.

Other issues that must be addressed include changes in purchasing, production planning and

control, and cost accounting practices. Arranging people and equipment into cells help

companies meet two goals of lean manufacturing: one-piece flow and high variety production.

These concepts dramatically change the amount of inventories needed over a certain period of

time.

• One-piece flow is driven by the needs of the customer and exists when products move through

a process one unit at a time thus eliminating batch processing. The goals of once-piece flow are

to produce one unit at a time continuously without unplanned interruptions and without lengthy

queue times.

• High-variety production is also driven by the needs of the customer who expect customization

as well as specific quantities delivered at specific times. Cellular manufacturing provides

companies the flexibility to give customers the variety they demand by grouping similar products

into families that can be processed within the same cell and in the same sequence. This

eliminates the need to produce products in large lots by significantly shortening the time required

for changeover between products.

In order to set up a single process flow (or single product flow) line, it is necessary to locate all

the different equipment needed to manufacture the product together in the same production area. 

This is in contrast with the traditional 'batch and queue' set-up wherein only similar equipment is

put in the same area.  Under a 'batch and queue' set-up, products that need to undergo processing

under certain equipment need to be transported to the area where the equipment is located. There

they are queued for processing in batches. Such a system sometimes results in transport and

batching delays.  In a single process flow set-up, the products simply transfer from one

equipment to the next along the same production line in a free-flowing manner, avoiding

transport and batching delays.

      

The single process flow set-up described above is an example of a 'work cell'.   A work cell is

defined as a collection of equipment and workstations arranged in a single area that allows a

product or group of similar products to be processed completely from start to finish.  It is, in

essence, a self-contained mini-production line that caters to a group of products that undergo the

same production process. Cellular manufacturing involves the use of work 'cells', which is how

it got its name.

                      

Since differently-processed products need different work cells, a large company with diversified

products needs to build several, different work cells if single process flows are desired.  Given

enough volume of products to work with, work cells have been proven by experience to be faster

and more efficient in manufacturing than 'batch and queue' systems. 

   

Because of the free flow of materials in cellular manufacturing, it has the ability to produce

products just in time. This means that every unit processed at one station will get processed in

the next station. As such, no inventories that have already undergone processing at one station

will be left unprocessed in another station.  This prevents the build-up of non-moving

inventories, which are products that have already incurred some production costs but can not

generate revenues because they are stuck somewhere along the process. Aside from preventing

non-moving inventories, process issues are immediately detected by just-in-time production,

since defective products are seen earlier than if products are manufactured in large batches and

queued.

   

One technique that cellular manufacturing can use to achieve 'just-in-time' production is the 'pull

system', wherein required inventories and materials are requested or 'pulled in' by each station

from the station preceding it.  This 'pull' can originate from the end customer itself, thereby

ensuring that the products manufactured are only those needed to satisfy a customer order. This

prevents wastes from products not being sold. 

         

It is not enough to simply arrange different equipment in sequence to make cellular

manufacturing really work.  Bottlenecks along the single process flow must be eliminated,

usually by balancing the equipment capacities with each other.  If bottlenecks exist, then the

higher-capacity equipment within the line will be underutilized. Balancing equipment capacities

may mean: 1) choosing 'right-sized' equipment that match each other; and/or 2) combining two

or smaller capacity equipment to match one larger-capacity equipment.

Literature Overview:

Case Study on Scheduling for Cellular Manufacturing Roman van der Krogt, James Little,

Kenneth Pulliam, Sue Hanhilammi, & Yue Jin (2007) found

Alcatel-Lucent is a major player in the field of telecommunications.

One of the products it offers to network operators is wireless infrastructure such as base stations.

Such equipment is delivered in cabinets. These cabinets are packed with various pieces of

electronics: filters, amplifiers, circuit packs, etc. The variation in cabinets is large, even within

one product group. For this reason, they are built to order. In order to improve cost, yield and

delivery performance, lean manufacturing concepts were applied to change the layout of the

factory to one based on cells. These cells focus on improving manufacturing through

standardized work, limited changeovers between product groups and better utilization of test

equipment.

A key component in the implementation of these improvements is a system which schedules the

cells to satisfy customer request dates in an efficient sequence.

This paper describes the transformation that supports the new method of operations which shows

improvements in manufacturing interval, work in process inventory, first test yield, headcount,

quality (i.e. fewer defects are found during the testing stage) and delivery performance.

Although these benefits are mainly achieved because of the change to a cell layout, the

scheduling tool is crucial in realizing the full potential of it.

The exact configuration of a cabinet is dependent upon the type of network (e.g. CDMA or

UMTS), the frequency (the GSM standard defines eight frequency bands, for example), physical

location (inside or outside), network density (is it expected to handle a high or low volume of

calls, what is the area the cabinet covers), etc.

The Systems Integration Center in Columbus, Ohio, produces several hundred cabinets per week

on average. The production takes place in three stages: assembly, wiring and testing. The

durations of each stage depends on the particular product group of the cabinet.

Assembly: The first series of steps takes as input a partially pre-populated cabinet.

Wiring: The second step involves physically interconnecting the hardware that was

added during assembly.

Testing: The final step involves the validation of the completed system.

Of the three stages, assembly is a relatively low skill operation and requires the least amount of

training. The wiring step is more complicated, because a great number of connections have to be

made between a great numbers of connectors that all look identical. There is a high degree of

freedom in the way the connections can be made. Not in terms of the inputs and outputs that

have to connected (these are fixed), but in terms of the order in which the connections are made

(i.e. which cables run in front of other cables), the position of the cables (e.g. along the left or the

right side of the cabinet) and which cables are tied together. The final step of testing is also

complicated, as it involves making diagnoses for the detected anomalies and repairing them.

The wirers and test engineers face a great difficulty because of the huge variety in cabinets.

Assembly puts populated cabinets into a buffer, from which the wirers take their cabinets. In

their turn, wirers put finished cabinets into a buffer for testing. In this situation, only a very crude

scheduling is employed. Based on the due dates of the orders, it is decided which orders are to be

produced on a given day. The assembly stage then starts populating the required cabinets and

places them in a buffer for wiring. When a wirer finishes a cabinet, he chooses one of the

cabinets from the buffer to work on. Similarly, testers pull a cabinet out of the buffer for testing.

In this way, cabinets trickle down the three stages on their way to completion. Aside from the

selection of which orders to produce on a given day, no scheduling is performed. This may lead

to several issues. Moreover, cabinets from product groups that are hard to wire may have to wait

in the wiring buffer for a long time, since other, easier, cabinets are preferred by the wirers.

To prevent these and similar issues, management had decided to move from what was essentially

an assembly line to a (partially) cell-based work floor. In particular, the company wanted to

integrate the wiring and testing activities into a cell, as depicted in Fig b.

From assembly line to cell-based work floor

Current Research

Constraint-based scheduling is a modeling and solving technique successfully used to solve real-

world manufacturing problems in, for example, aircraft manufacturing, production scheduling

and the semiconductor industry. In the area of telecommunications, the area of cellular

manufacturing is more about layout and design. The Author Ponnabalam et al.consider

simulation of manufacturing through a cell in light of uncertainty. They propose new heuristics

to decide on the allocation of jobs to machines. Here the user interface is built in Microsoft Excel

using Visual Basic. It allowed for easy integration with the existing Work floor Management

System that tracks all activities and can generate reports in the Excel file format for initial

modeling and getting the feedback on that model. The amount of work it takes to go from

prototype to a system robust is enough to withstand user interaction which allows for different

input profiles. In this case it is important to make the user realize that the initial phase of testing

will be slow and not very smooth at times, as the tool is adjusted to match the reality on the shop

floor.

Future Research Work

This project shows the strength of the combination of lean manufacturing techniques and (CP-

based) scheduling. The former techniques allow a business to take a critical look at its operations

to identify areas for improvement, whereas the latter technique can be used to realize the

potential of the improvements.

The amount of constraints the program has to handle points out the need for it. Scheduling

manually would not allow us to service our customers as well. The engineers at the site had

experience with the Theory of Constraints to help greatly in the initial modeling and getting the

feedback on that model. The amount of work it takes to go from prototype to a system robust

enough to withstand user interaction is considerable. Moreover, the variety of situations that is

encountered in practice means that the model itself has to be robust enough to allow for very

different input profiles. This either calls for a large data set during development, or a period of

building this robustness during the testing process. In this case it is important to make the user

realize that the initial phase of testing will be slow and not very smooth at times, as the tool is

adjusted to match the reality on the shop floor.

Related Journals Supporting the above Literature Review:

Partitioning bottleneck work center for cellular manufacturing: An integrated performance and

cost model (Atul Agarwal, 2007)

The objective of this paper is to investigate performance and cost issues in an integrated manner

during conversion of an existing functional layout by partitioning it to a corresponding cellular

manufacturing (CM) layout. Decision frameworks presented which provides a systematic

approach to a practitioner for such a conversion. A total cost model is developed to study the

performance and financial aspects for the CM system. The relationship between setup time

reduction and the operational characteristics of a cell is also examined. A simple case study from

a small manufacturing organization is used to evaluate the practical dimensions of the model and

study results.

A decision support tool to facilitate the design of cellular manufacturing layouts V. Vitanov, B.

Tjahjono, & I. Marghalany (2007) found

This paper presents a decision support tool that can be used by practitioners and industrialists to

solve practical cell formation problems. The tool is based on a cell formation algorithm that

employs a set of heuristic rules to obtain a quasi-optimal solution from both component routing

information and other significant production data. The algorithm has-been tested on a number of

ata sets obtained from the literature. The test results have demonstrated that in many cases the

algorithm has produced an exceptional performance in terms of the grouping efficiency,

grouping efficacy and quality

Index measures. The algorithm, to an extent, overcomes common problems in existing cell

formation methods such as in dealing with ill-structured matrices and achieving rational cell

sizes.

A genetic algorithm for cellular manufacturing design and layout Xiao Dan Wu, Chao-Hsien

Chu, Yunfeng Wang, & Weili Yan (2006) found

Cellular manufacturing (CM) is an approach that can be used to enhance both flexibility and

efficiency in today’s small-to-medium lot production environment. The design of a CM system

(CMS) often involves three major decisions: cell formation, group layout, and group schedule.

Ideally, these decisions should be addressed simultaneously in order to obtain the best results.

However, due to the complexity and NP-complete nature of each decision and the limitations of

Traditional approaches, most researchers have only addressed these decisions sequentially or

independently. In this study, a hierarchical genetic algorithm is developed to simultaneously

form manufacturing cells and determine the group layout of a CMS. The intrinsic features of our

proposed algorithm include a hierarchical chromosome structure to encode two important cell

design decisions, a new selection scheme to dynamically consider two correlated fitness

functions, and a group mutation operator to increase the probability of mutation. From the

computational analyses, these proposed structure and operators are found to be effective in

improving solution quality as well as accelerating convergence.

A goal-programming approach for design of hybrid cellular manufacturing systems in dual

resource constrained environments (Sule Itir Satoglu & Nallan C. Suresh, 2008)

In this study, a goal-programming model is proposed for the design of hybrid cellular

manufacturing (HCM) systems, in a dual resource constrained environment, considering many

real-world application issues. The procedure consists of three phases. Following an initial phase

involving a Pareto analysis of demand volumes and volatility, a machine-grouping phase is

conducted to form manufacturing cells, and a residual functional layout. In this phase, over-

assignment of parts tithe cells, machine purchasing cost, and loss of functional synergies are

attempted to be minimized. Following the formation of cells and the functional layout, a labor

allocation phase is carried out by considering worker capabilities and capacities. The total costs

of cross-training, hiring, firing and over-assignment of workers to more than one cell are sought

to be minimized. An application of the model on real factory data is also provided in order to

demonstrate the utility and possible limitations. The industrial problem was solved using

professional mathematical programming software.

A new approach for the cellular manufacturing problem in fuzzy dynamic conditions by a genetic

algorithm R. Tavakkoli-Moghaddama, M.B. Aryanezhad, N. Safaei, M. Vaseia, & A. Azaronc

(2007)

This paper presents a fuzzy linear mix-integer programming model for design of cellular

manufacturing systems with fuzzy part demands and product mix changeable under a multi-

period planning horizon. In this dynamic condition, the best cell design for one period may not

be efficient for subsequent periods and the reconfiguration of cells is required. The proposed

model can determine the production volume for each part considering its fuzzy demand. The

other advantages of the proposed model are as follows: considering inter-cell material handling

with constant batch size, alternative process plan forepart types, operation sequence, machine

relocation, machine replication, machine utilization and cell number flexibility. Main constraints

are the cell size, machine capacity and production volume limitations. The objective is to

minimize the sum of the constant/variable/relocation machine costs as well as inter-cell

movements cost. Because of the complexity of the proposed model, which is a combinatorial

nonlinear optimization, we develop an efficient genetic algorithm with novel representation and

Operators for solving the proposed model. 29 small, medium and large-sized problems are

generated to evaluate the performance of the proposed model and the efficiency of the developed

genetic algorithm.

An algorithm for cellular manufacturing system and layout design using sequence data (Iraj

Mahdav & B.Mahadevan, 2007)

Cell formation problem in CMS design has received the attention of researchers for more than

three decades. However, use of sequence data for cell formation has been a least researched area.

Sequence data provides valuable information about the flow patterns of various jobs in a

manufacturing system. Therefore, it is only natural to expect that use of sequence data must

result in not only identifying the part families and machine groups but also the layout (sequence)

of the machines within each cell. Unfortunately, such an approach has not been taken in the past

while solving CMS design problem using sequence data. In this paper, we fill this gap in the

Literature by developing an algorithm that not only identifies the cells but also the sequence of

machines in the cells in a simultaneous fashion. The numerical computations of the algorithm

with the available problems in the literature indicate the usefulness of the algorithm. Further, it

also points to the untapped potential of such an approach to solve CMS design and layout

problem using sequence data.

An optimal design approach for a cellular manufacturing system R Giri, J Srinivas, & K V V C

Mouli (2007) found

The current paper proposes an optimum clustering approach for automatic generation of machine

cells and part families. The design of a cellular manufacturing system begins with a specified

‘part-machine incidence’ matrix, showing the machine sequence and volume of production. The

arrangement of machines in the cells is addressed in the present paper by finding an optimal

machine sequence, which maximizes the overall flow of components between the machines. An

optimal number of cells are arrived heuristically by accounting the total intercool movements

using the obtained machine sequence. The methodology is illustrated with examples.

Cellular manufacturing—A time-based analysis to the layout problem (Mechanical Engineering

Department, [N.I.T], 2007)

A cellular manufacturing system is an application of group technology principles to production.

This involves processing groups of similar components in a dedicated cluster of dissimilar

machines. In this paper, an approach that forms the cluster based on the processing time is

suggested. For even distribution of workload, workload balancing is carried out in the second

phase of the model, i.e., a time-based model. The time-based model is compared with the

workload-based model using a commonality score. The performance of the time-based model is

compared by means of workload deviation and deviation index. The validity of the approach is

tested by application to the problems from the literature and the results are presented. The results

indicate that the time-based model gives better even distribution of workload as compared to the

workload-based model.

Layout designs in cellular manufacturing (Massoud Bazargan-Lari, 1997)

Cellular manufacturing (CM) is now an established international practice to integrate:

equipment, people, and systems into `focused factories', `mini-businesses' or `cells' with clear

customers, responsibilities and boundaries. The major elements in exploiting the beets of CM are

client layout designs. This paper presents the application of recently developed multi-objective

inter- and intra-cell layout designs methodologies in a CM environment by the author

To a dynamic food manufacturing and packaging company in Australia. Some of the problems

expressed by the company were large and unnecessary volume of shop floor material handling

cost, diculties and confusion overproduction planning, long products lead times resulting in

losing customers and high overhead costs. Furthermore the company was deeply concerned

about the increasing number of accidents and injuries on the shop floor caused by poor

Layout of machinery and the lack of proper aisle structures for movement of the lift-trucks. This

paper shows the process of developing the inter-cell layout designs by providing the

management with multiple layout configurationsand showing the impact of each design on the

material handling cost at each stage. These solutions not only provide a safer shop floor but also

signi®cant reductions in material handling cost, waste, need for large capital investment and the

number of lift-trucks needed on the shop Floor.

Reliability consideration in the design and analysis of cellular manufacturing systems (K. Das, S

Lashkari, & S. Sengupta, 2006)

A multi-objective mixed integer programming model of cellular manufacturing system (CMS)

design is presented which minimizes the total system costs and maximizes the machine

reliabilities along the selected processing routes. A part maybe processed under different process

plans, each prescribing a sequence of operations to be performed at various machines in a serial

configuration. Thus, each process route is associated with a level of reliability corresponding to

the machines in the selected process plan. The CMS design problem consists of assigning the

machines to cells, and selecting, for each par type, the process route with the highest overall

system reliability while minimizing the total costs of manufacturing operations, machine under-

utilization, and inter-cell material handling. The proposed approach provides a flexible routing

Which ensures high overall performance of the CMS by minimizing the impact of machine

failure through the provision of alternative process routes in case of any machine failure? The

paper also proposes performance evaluation criterion interims of system availability for the parts

and process plan assignments. Numerical examples are provided to demonstrate the applicability

of the model.

The evolution of a cellular manufacturing system – a longitudinal case study (cult of

Management and Organization, University of Groningen, 2001)

This paper describes the evolution of a cellular manufacturing system in a medium-sized

company over a 13-yearperiod. The objective of this paper is to analyze the arguments that gave

rise to the nearly continuous readjustment of the design of the cellular manufacturing system of

this company and the direction in which these adjustments took place. The study indicates that

two interrelated factors played an important role in the decision to change the system:

The market and manufacturing technology. Analysis of these factors offers important insights

into the aspects that need to be taken into account in cell formation. It is argued that a cellular

system should reflect market characteristics. New technology, furthermore, demands specialized

cells, producing in a multi-shift situation. These two developments pointing the direction of

market-oriented, reasonably sized, functionally organized manufacturing units. It is argued that

Market developments, new manufacturing technology and modern production control systems

will probably constraint the application area of cellular manufacturing

Multi-period planning and uncertainty issues in cellular manufacturing: A review and future

directions (Jaydeep Balakrishnan &hun Hung Cheng, 2006)

In this paper we review research that has been done to address cellular manufacturing under

conditions of multi Period planning horizons, with demand and resource uncertainties. Most

traditional cell formation procedures ignore any changes in demand over time caused by product

redesign and uncertainties due to volume variation, part mix variation, and resource unreliability.

However in today’s business environment, product life cycles are short, and demand volumes

and product mix can vary frequently. Thus cell design needs to address these issues. It is only

recently that researchers have been modeling uncertainty and multi-period issues. In this paper

we conduct a comprehensive review of the work that addresses these issues. We present

mathematical programming formulations as well as taxonomy of existing models. Finally we

suggest some directions for future research

References:

Partitioning bottleneck work center for cellular manufacturing: An integrated performance and

cost model (Atul Agarwal, 2007)

Scheduling for Cellular Manufacturing Roman van der Krogt, James Little, Kenneth Pulliam,

Sue Hanhilammi, & Yue Jin (2007) found

A decision support tool to facilitate the design of cellular manufacturing layouts V. Vitanov, B.

Tjahjono, & I. Marghalany (2007) found

A genetic algorithm for cellular manufacturing design and layout Xiaodan Wu, Chao-Hsien Chu,

Yunfeng Wang, & Weili Yan (2006) found

A goal-programming approach for design of hybrid cellular manufacturing systems in dual

resource constrained environments (Sule Itir Satoglu & Nallan C. Suresh, 2008)

A new approach for the cellular manufacturing problem in fuzzy dynamic conditions by a

genetic algorithm R. Tavakkoli-Moghaddama, M.B. Aryanezhad, N. Safaei, M. Vaseia, & A.

Azaronc (2007)

An algorithm for cellular manufacturing system and layout design using sequence data (Iraj

Mahdav & B.Mahadevan, 2007)

An optimal design approach for a cellular manufacturing system R Giri, J Srinivas, & K V V C

Mouli (2007) found

Cellular manufacturing—A time-based analysis to the layout problem (Mechanical Engineering

Department, [N.I.T], 2007)

Layout designs in cellular manufacturing (Massoud Bazargan-Lari, 1997)

Reliability consideration in the design and analysis of cellular manufacturing systems (K. Das,S

Lashkari, & S. Sengupta, 2006)

The evolution of a cellular manufacturing system – a longitudinal case study (culty of

Management and Organization, University of Groningen, 2001)

Multi-period planning and uncertainty issues in cellular manufacturing: A review and future

directions (Jaydeep Balakrishnan &hun Hung Cheng, 2006)