process understanding and improvement through...

Process Improvement through SPC 1Norman Greig

CCS Associates Limited SPC & Process Improvement Consultants

Tectona House, Great Dunmow, Essex , CM6 2AT

tel./fax: 0044 (0) 1371 859 200 www.ccsassociates.com [email protected]

An introduction to SPC tools and techniques and how they can be used to understand and improve processes (and increase profits)

SPC & PROCESS IMPROVEMENT © 2006-2010 CCS Associates Ltd. Norman Greig 1

Process understanding and improvement through SPC

Norman GreigCCS Associates LimitedTectona House

Dunmow,

Essex, CM6 2AT, UK

Tel/fax +44 (0)1371 859200

Contact: Norman Greig

[email protected]

www.ccsassociates.com

SPC concepts and key tools

SPC as a basis for quality control & process control

Types and causes of variability and which ones to tackle first

Selecting and understanding control charts for variables and attributes

Types of control charts and how to interpret them

How to set limits and targets for control charts

Introduction to Pareto Analysis- sorting the vital few from the trivial many

Process Capability - what is it and how to measure it

FMEA: Key steps in Process Failure Mode and Effects Analysis

The next steps in implementing SPC


Process understanding and improvement through SPC

What are Today’s challengesin manufacturing?

• Getting information about a process NO

SPC & PROCESS IMPROVEMENT © 2006-2010 CCS Associates Ltd. Norman Greig

• How to get more value from all the data that is already being collected.

• Understanding the process and getting the right information to the right people at the right time

3

Statistical Process Control

Process Analytical Techniques


Traditional QC v SPC


The Product

equipment materials

environmentmethods

people

The Process

Information

about

performance

Action on

the PROCESS

Information about

the product

Action on

the product

Traditional Quality ControlStatistical Process ControlWhy Statistics?

Allows conformity

to be judged

objectively

Allows sensible sampling

plans to be designed

Predictions can be

made with known

precision and risk

More economical






What is Statistical Process Control?

Statistical Process Control is the application of simple statistical methods to measure and

control this variability during manufacture

Variability is inherent in every manufacturing process, which causes product to vary – even

if only slightly


Sources of variation – causes


Types of Variation in the Process


PERFECT CONSISTENCY IN A PROCESS IS NOT

ATTAINABLE

TO MANAGE A PROCESS WITHIN AN ACCEPTABLE

VARIATION THE CAUSE OF THE VARIATION MUST BE

DETERMINED AND QUANTIFIED

Piecing together the SPC puzzle -

Types of causes of variation:

Common Causes:

(Random Variation)

Many small sources

Stable & relatively predictable

Permanent unless action taken.

Assignable Causes

(Special

Disturbances)

One of few major

causes.

May be irregular

May reappear unless

action taken

Stages of Process Improvement


Example SPC techniques & tools

SPC & PROCESS IMPROVEMENT © 2006-2010 CCS Associates Ltd. Norman Greig

Process

flow

chart

x

x x

x

x

x

scatter diagram

55

12

55

10

Tally chart

Brainstorm - cause & effect

Histogram

mean & range charts

Pareto chart

12

Control charts for measurement variables

• Setting values for centre line, upper and lower limits.

• The differences between control limits and specification limits

• Interpreting charts - when to act - when to leave well alone

• Finding Cause and Effect and taking corrective actions

• Continuing process improvement

– bringing control limits closer together






Control charts for measurement variables


Upper Control LimitUpper Action Limit

Lower Action Limit Lower Control Limit

UCL

UWL

LWL

LCL

Types of Attribute Control Charts


Result within/outside specification

Lid sealed Yes/No

Presence/absence of required safety label

p chart for proportion of units non-conforming (sample size can vary)

np chart for number of units non-conforming (samples of equal size)

Defectives Type of Control Chart

Underweight

Overweight

Damaged container

Pinholes in a container

u chart for number of non-

conformities per inspection

unit (sample size can vary)

c chart for number of non-

conformities (samples of

equal size)

Defects

Attribute Chart - example


Pareto Chart - example


Run Pareto defects

Measuring process and product performance - capability

The difference between "in control" and "out of control"

What is an incapable process - what is a capable process

Measures of process performance - potential capability v process performance

Corrective actions - Adjusting Process settings -process mean and variation


The Normal Distribution


95%

+2 SD-2 SD

-3 SD +3 SD

2.2%

2.2%

99.7%

Process Spread 6 x SD

LSL USL





What is a capable Process?

• Potentially Capable Cp => 1

The process spread (6 x SD) does not exceed the tolerance (USL-LSL)

• Actually Capable (Process Performance) Cpk => 1

This takes account of the process mean and target


Process capability example


Advanced skills in process improvement


How to plan and implement Process FMEA

Key factors for sampling plans

How to set specification limits and targets for production

The merits of the various types of control charts and how to choose the most appropriate chart

Improving the process

Quality Risks and FMEA


Types of Quality Risk

Quality

Dissatisfied Customers

Scrap Production

Product Held

Loss of Certification

Business

Breach of Regs.

Bad Publicity

Failure of the Process

Disruption to the Process

Lost Time

Financial Cost

Risk of Litigation

Key steps in FMEA(the SFC model)Assemble cross functional team – all disciplines represented

Identify the process –flow chart

Identify potential failure modes – existing knowledge and brainstorm

List potential effects of failure

Rank the (S)everity – consequences of failure

Assign (F)requency rankings – how often is it likely to happen (or L(ikelihood)

Assign (C)ontrol - how likely to be detected before reaching customer

Calculate Significance Number (RPN)—S x F x C – (or could be L x S) - set priority level

Identify improvement actions and make action plan(s) – what, who when

Take the improvement actions

Evaluate the effectiveness of the actions – recalculate RPN of potential failure modes





Make Action Plans

Prioritise risk items by RPN/significance

Assign tasks to reduce risk scores

Define S.M.A.R.T. Targets

Make the action plan

Improvement and analysis tools

• Mistake proofing (Poka Yoke)

• SPC, Statistical Process Control

• Control charts, process capability

• DOE, Design of Experiments

Main types of Control charts and selecting

Type of Data Type of Chart Use of Chart

Variable (measure how much)

Individual moving range (I-mR)

Each subgroup is 1 measurement

Average - range (x-bar R)The subgroup consists of 2 to 10 measurements

Average - standard deviation (x-bar s)

The subgroup consists of 10 or more measurements

Attribute (count how many)

p chart (defectives) Proportion defective

np chart (defectives) Number defective

c chart (defects) Defects per sub group

u chart (defects) Defects per unit

Individual moving range (I-mR)

Any type of attribute data


Analysing problems with charts and plots

SPC & PROCESS IMPROVEMENT © 2006-2010 CCS Associates Ltd. Norman Greig32

Example: Identify source of variation In fill weight – food industry

Analysing problems with charts


Cost savings: Product give away – overfillThis plot could save £1000’s


Cost savings: Product give away – overfill


bag fill target +- 2% 50 kg +- 1kg overfill % 0.36mean 6 months 50.18 overfill kg 0.18bag t bags no. $/tonne $/kg kg saved $ saved target

686000 13,720,000 50 0.05 0.05 $34,300+-2%686000 13,720,000 50 0.05 0.1 $68,600686000 13,720,000 50 0.05 0.15 $102,900686000 13,720,000 50 0.05 0.18 $123,480686000 13,720,000 50 0.05 0.2 $137,200

$34,300

$68,600

$102,900

$123,480

$137,200

$0

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

$140,000

$160,000

0.05 0.1 0.15 0.18 0.2

kg saved per bag

$ saved





• Example: Pet Food Giveaway

• Problem: Overfill leading to excessive product giveaway.– A manufacturer of premium dry pet food is producing 17

million kg (10,011,808 packages) of product per year, 370525 kgs (or 27 truckloads) of which is overfill, resulting in £871,477 in product giveaway costs.

• Action: Understand the specifications and the process and improve the process.– Identify sources of variation leading to overfill

– Reduce variation and adjust target values

– Monitor process Improvements


Understand and control the process, save moneyOverfill - Pet Food • Avg. Fill wt per pkg = 1.739

• Net wt declaration = 1.702 avg. overfill per pkg = .037kg

• Overfill = (10,011,808 pkgs/yr) x 0.037 = 370,526 kgs of overfill per year

• Cost of Overfill = (370,526 kgs/yr) x (£2.352/kg) = £871,477 p.a.

1. Savings: The manufacturer identified and corrected the causes of the overfill and gained tighter control of its process, allowing it to eliminate 50% of its giveaway costs, or

£435,739 per year1. Payback: 10.7 days to fully pay the investment in SPC.

• Payback = (£15,000/£435,739) x 312 production days per year = 10.7 days to payback

Benefits - savings £435,739 per year, Payback 10.7 days


Results: Reduced Overfill - Pet Food


Results: Reduced Overfill - Pet Food

£0

£50,000

£100,000

£150,000

£200,000

£250,000

£300,000

£350,000

£400,000

£450,000

£500,000

1 2 3 4 5 6 7 8 9 10 11 12

Cost savings after SPCpet food fill

Months Average saving £

Complaints- Pareto by frequency and cost International shipping & trading


Pareto analyses allows company to:

• Identify most significant complaints & systematic errors

• Improve management system for finding cause & effect & cost

• Implement system for follow up and close out

• Identify action to prevent re-currence

• Include follow up in monthly management meetings

• Assign ownership of issues to relevant people

• Set targets and actions plans for reduction in complaints


Results: Complaints management benefitsDefects- Pareto and Attribute chart






Role of SPC in Holistic approach to process understanding - pharmaceuticals

Process:

slow release

spheroid production


QC Analysis

MANUFACTURING PROCESS

REACTIVE &

RETROSPECTIVE

Link to holistic SPC article

http://www.ccsassociates.com/sitebuildercontent/sitebuilderfiles/qmtnappjul08.pdf

Determine the dissolution rate.

If it is too fast continue film coating until

a satisfactory dissolution rate is achieved

Role of SPC in Holistic approach to process understanding - pharmaceuticals

Tools: charts, fishbone diagrams and

brainstorming were the main tools used to

understand the variation in the various stages of the process.

The steps were:

• Form Continual Improvement Team (CIT)

• Gather data and plot on a chart

• Analyse performance

• Identify cause and effect

• Make improvements

• Monitor to find if improvement is effective


Cross Functional Team requiredQC,QA,Manufacturing Operators,Engineering,Trainers,

Process Analysts

•Investigate and eliminate special cause variation

•Identify and eliminate possible failure modes

•Reduce common cause variation

With acknowledgement to Tom Cochrane, Napp

Stop tampering – improve the process


ADIZEM XL SPHEROIDSTOTAL DRYING TIME

Individ.: cl: 48.2 ucl: 65 lcl: 31Subg rp Size 1

MIN

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109666

110182

110432

FIXED TIME OF 50 MINUTES

Individ.

cl

lcl

ucl

20

40

60

80

100

120

140

BATCHNO: 106495 108172 110183 111967 113355 114510 117337 118957 119929

Introduced fixed time rather

Than drying to an outlet temperature

Improved equipment

Laser drilled screen

fitted

Stopped Tampering

Reduced Waste

Improve equipment – Sieving

Wt. oversized

Improved Yields

Stopped Tampering





Dissolution profile and window


window

CIT Activity Starts

Benefits of process improvements Napp Pharmaceuticals

Overall benefits can be tangible as in cost savings but it is often the intangibles which give the greatest value.

1. Dissolution Right First Time improved from 79% to 97% avoiding re-coating.

2. 3-4% Increase in yield– Added value: improved laboratory and production capacity– Reduced waste– Improved morale and confidence in the process and product– Charts pick up machinery problems quicker– Through using the charts users can see a visual representation of each

process step allowing a forum for discussion and continuous improvement

3. Overall cost benefit

– £2 million extra product per annum


CCS Associates Ltd.Consultancy, Training and Software. Process Capability & Improvement Programmes

Process Analytical Techniques

Statistical Process Control Statistical Quality Control

NWA SPC software solutions & system integration

ISO 14001 Environmental ISO 9001 Quality Product Certification


Norman GreigCCS Associates LimitedTectona HouseDunmow, Essex, CM6 2AT, UKTel/fax +44 (0)1371 859200 Contact: Norman Greig

[email protected]

www.ccsassociates.com

Thank You

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