Process Oriented Quality Control Tools and Techniques

October 13th, 2011 S P Dikshit 1

Process Oriented Quality Control Tools and Techniques

I2IT, Pune

One-Day Seminar On Industrial Applications Of Statistical Software in Quality Management and Reliability Engineering

October 13th, 2011

Process Oriented Quality Control

In this lecture we will see shortcomings while using

process approach in the quality management. Change

required in organizational structures, creating team with

competences. Linking remuneration with results and not

just according to work. We will also see procedure of

phase building of the process oriented quality control

system. We will also go through some quality tools used

for Quality Improvement.


Quality History

There are lessons to be learned from the

experiences of the successful companies.

The common factors are: Focusing on

customer needs, upper management in

charge of quality, training the entire

hierarchy to manage for quality, and

employee involvement

- Joseph Juran, World War II and the Quality Movement


Bell Laboratories where modern quality management evolved. Both Deming and Juran worked for BellWalter Shewhart: Process Oriented Quality Control

ASQC was established at 1946 changed to ASQ in 1996Attitude changed manufacturer can sell whatever they

produce. Why quality?Japanese (quality in culture)- trouble for rest of the

world.Poor Quality - Motorola and Whirlpool TQM Concept emerged (1980). Early TQM Success –

Xerox, Motorola, Intel, Corning, Hewlett-PackardSix Sigma.Design for Six SigmaLean Six Sigma.


Quality History

Process Oriented Quality ControlPhase 1. •Create own strategy based on future processes of the company.•Define key qualifications.•Define critical success factors.

Phase 2. •Determination of the requirements on processes.•Clearly determine requirements on individual processes.•Determine links among the processes.


Process Oriented Quality ControlPhase 3. Determining criteria for individual

processes. Determine criteria that will clearly show

performance and efficiency of the management of individual processes.

Phase 4. Integrate process in a value creating

chain adding value for the customer.


Heroic Method of Problem Solving?

People are working hard. Typical fire fighting.Sensing a problem.Some sort of new emergency arises, interrupting

what is happening already.Dither — waste time on inter mural squabblingHeroic efforts take place to deal with the new

emergencyDeclare a solution — usually by someone in a

position of authorityPeople go back to what they were doing beforeForget about it — nothing changes


Correct Blending Theory and experienceSense the problemExplore situation.Collect data.Formulate problemChoose specific improvement process/ theme.Collect and analyze data.Analyze causesPlan probable solutionExperiment/ Try it.Collect new dataEvaluate effectsStandardize solution.


Proactive

Reactive

Control


Problem Solving

Quality Process Improvement

Problem Solving

Successful results

Improvement Project execution Tools

Skill gaining Tools

Analysis Tools

Quality function deployment (QFD) QFD is a “method to transform user demands into design quality, to

deploy the functions forming quality, and to deploy methods for achieving the design quality into subsystems and component parts, and ultimately to specific elements of the manufacturing process

A failure modes and effects analysis (FMEA) FMEA is a procedure in product development and operations

management for analysis of potential failure modes within a system for classification by the severity and likelihood of the failures.

5 Ss - Hirano

Methods of keeping a work area organized for maximum productivity.

7 QC Steps (QC Story) - Kume (191-206), Brassard 1994 (115-122), CQMc, Karatsu (11-13)

A set of steps to follow in solving many kinds of problems (also used to report on the improvement process).


Tools and Techniques

Tools and TechniquesCause-and-effect diagram (or Ishikawa or fishbone diagram)

- Brassard 1994 (23-30), Wadsworth (310-313), Kume (25-33), Ishikawa (18-29), Karatsu (62-83)

Organizes data in terms of cause-and-effect such that the root cause of a situation may be revealed.

Benchmarking - Spendolini

Comparing your process with a "best in class" process to learn how to improve your process.

Analysis of variance - Wheeler 1990 (83-110)

Comparing various estimates of variation among subgroups to detect differences between subgroup averages

Brainstorming - Brassard 1994 (19-22)

Allows a team to creatively generate ideas about a topic in a judgement free atmosphere.

Check sheet (tally sheet) - Brassard 1994 (31-35), Wadsworth (292-300), Kume (91-134), Ishikawa (30-41), Ozeki (159-169), Karatsu (44-61)

Tallies (e.g., ||||) of problems or characteristics appropriately organized on a page.


Arrow diagram - Ozeki (273-280)

Shows the network of tasks and milestones required to implement a project.

Affinity diagram - Brassard 1989 (17-38), Brassard 1994 (12-18), Ozeki (246-250)

Organizes ideas and issues so as to understand the essence of a situation and possible follow-on actions.

Capability measures and ratios - Brassard 1994 (132-136), Wheeler 1992 (117-150)

Various ratios and measures of the natural variation of process outputs

(for instance, 3 standard deviation limits) and specification limits.Causal loop diagram - Senge (87-190)

A more sophisticated cousin of a relations diagramCentral tendency and dispersion of data - Wadsworth (74-80), Wheeler

1992 (22-26), Ozeki (185-194), Kume (143-156)

Measures of the location and spread of data, e.g., mean and standard

deviation, median and range, etc.



Control chart - Brassard 1994 (36-51), Wadsworth (113-284), Wheeler 1992 (37-350), Ishikawa (61-85), Ozeki (205-235), Karatsu (131-157), Kume (92-141)

Quantifying variation and separating signal from noise. Typically used to monitor that a process is continuing to operate reliably; also used to detect if a change to a process has had a significant effect.

Design of experiments – Box, Lochner

Strategies for selecting a limited number of runs (observations of responses) in a possibly high-dimensional factor space so as to gain the maximum information about how the response values depend on the factors.

Flow chart – Brassard 1994 (56-62), Wadsworth (320-324)

Graphical representation of the steps in a process or project. Graphs and graphical methods - Ishikawa (50-60), Ozeki (121-137),

Karatsu (158- 217), Wadsworth (325-351)

Many different techniques for showing data visually and analyzing it.



Histogram – Brassard 1994 (66-75), Wadsworth, (300-306), Wheeler 1992( 27-30), Kume (37-66), Ishikawa (5-17), Ozeki (172-178), Karatsu (116-131)

Shows the centering, dispersion, and shape of the distribution of a collection of data.

Language Processing diagram - CQMa

A more structured and effective version of an affinity diagram, derived from the same source as the affinity diagram (Jiro Kawakita's KJ diagram).

Pareto chart (analysis, diagram) - Brassard 1994 (95-104), Wadsworth (306-310), Kume (17-23), Ishikawa (42-49), Ozeki (139-147), Karatsu (24-43)

Data sorted in order of decreasing frequency of events and with other annotations to highlight the "Pareto effect" (e.g., the 20 percent of the situations that account for 80 percent of the results).



Poka-yoke (mistake proofing)- Shingo

Methods to prevent mistakes from happening. Process decision program chart (PDPC) - Brassard 1989

(167-196), Breasard 1994 (162)

Explicitly lists what can go wrong with a project plan (organized in a tree diagram) and provides appropriate counter-measures.

Process discovery - Shiba (95-106)For an activity, making explicit the customers, products

and services, needed inputs, customer requirements and measures of satisfaction, process flow, and so forth.

Regression analysis - Brassard 1989 (39-70)

Analyzing the relationship between response (dependent) variables and influencing factors (independent variables).



Run chart or record - Brassard 1994 (141-144), Wheeler 1992 (32),Wadsworth (313-320)

A version of a scatter (x-y) plot where data values over time (the x axis) are plotted (on the y axis).

Scatter (or x-y) diagram (plot) - Brassard 1994 (145-149), Kume (67-86), Wadsworth (313-320), Ishikawa (86-95), Ozeki (237-243), Karatsu (106-115)

A graphical way of showing correlation between variables. Sampling - Ishikawa (108-137), Breyfogle 1999 (6, 294-335); see also indexes

of Grant, Wadsworth, and Wheeler 1992

Selecting a few instances from a set of events from which to infer characteristics of the entire set.

Statistical tests - Kume (157-190), Breyfogle 1992, Breyfogle 1999 (6, 294-335)

For instance, various ways of testing hypotheses.



Stratification of data – Pande (chapter 14), Ozeki (179-183)

Classification of data from multiple viewpoints, such as what, where, when, and who.

Tree diagram - Brassard 1989 (97-130), Brassard 1994 (156-161),CQMb, Ozeki (257-263), Karatsu (96-105)

Organizes a list of events or tasks into a hierarchy. Relations diagram - Ozeki (251-256), Karatsu (84-95), Brassard 1989

(197-229); see also Brassard 1994 (76-84)

Shows a network of cause-and-effect relationships. Queuing theory - Reinerston (42-67), Hall

Analysis of delays and waiting lines. Matrix data analysis – Mazuno (197-215)

Various multivariate analysis methods. Matrix diagram - Brassard 1989 (131-166), Brassard 1994 (85-90),Ozeki

(265-272)

Shows multi-dimensional relationships. October 13th, 2011 S P Dikshit 17


ReferencesArticles Quality Process Improvement Tools and

Techniques Shoji Shiba and David WaldenPROCESS ORIENTED QUALITY

ASSURANCE Adkinson, James D., P.E.Process Oriented Quality Management

System Alexander Linczényi, Renáta Nováková



Questions ?


Deming Dr. W. Edwards Deming was a statistician and a student of Dr. Shewhart. His early career was spent teaching the application of statistical concepts and tools within industry. Latterly he developed a theory of management and "Profound Knowledge". Deming was well known to the Japanese and their national award for quality management was named for him. He remained largely unknown in his native USA until he was 'discovered' by the media in 1981. He continued to write and to deliver his four-day seminar (with the famous 'red bead' experiment) until his death in 1993.


Juran Dr. Joseph Juran is a management consultant and a prolific author whose hallmark is a common-sense, practical approach. Like Deming he was instrumental in helping the Japanese to learn and apply quality management in the 1950's. He has written and edited a number of authoritative books and countless articles. He is also the founder of the Juran Institute, a research and consulting organization.


Crosby Phil Crosby was a highly successful quality manager

within ITT, and rose to become an executive.

Approaching retirement, he wrote "Quality is Free",

which was an immediate best-seller, and he went on

to establish a training and consulting company. One of

the key features of Crosby's approach is the use of

financial indicators of waste (e.g. the cost of poor

quality) to capture management's attention.


Malcolm Baldrige

Malcolm Baldrige is not generally considered to be one of the quality management 'gurus' (he was the US Secretary of Commerce from 1981 to 1987) – but the creation of the award named for him was one of the landmark events in rekindling interest in quality management in North America. The Baldrige award criteria is an important tool that defines the elements of an effective, customer-focused management system based upon quality principles. It is widely used for educational and assessment purposes.


Shewhart

Dr. Walter A. Shewhart is considered the father of Statistical Process Control (SPC). Shewhart worked in Bell Laboratories and was engaged in a search for practical methods of quality control for the emerging telephone industry, which required mass production on a huge scale. His ideas, published in the 1930's, formed the basis for a system/process oriented approach to quality control, by viewing any repetitive activity as a process and using statistics to understand and to manage the variations that will always occur.


Process Oriented Quality Control Tools and Techniques

Documents

tree diagram

day seminar

affinity diagram

october 13th

joseph juran

quality control

poor quality

quality management