Quality management Lecture 3. Quality theories Quality management Lecture 3.

History of quality management Early 1920 Scientific management (Taylor, Gilbreth) 1920s Statistical process control (Shewart) 1930s Acceptance sampling (Dodge, Roming) 1940s Military standards introduced 1950s Quality management in Japan (Deming, Juran) 1960s Taguchi method, and quality tools 1970s Quality becomes strategic (USA) 1980s Introduction of LEAN, TQM, Baldrige Award 1990s Reengineering, Six Sigma 2000s Supply chain management, improvement of supplier development, LEAN, Six sigma become popular, contingency theory

Quality and taylorism Basics of taylorism Quality effects: The whole process is divided into short steps (division of labor) It is not the worker who determine the process/movements -specialist do that (task management) Workers are selected and trained for work Standard movements and tools, detailed instructions (standardization) Quality effects: Product and process design were separated from the repair of product Workers were not responsible for repairing of product Quality control department was established to control the product at the end of the process The responsibility for quality were spread over in the company

Deming Not just worker but managers have the responsibility for establishing quality Workers responsible for special problems Managers responsible for the whole system (proper methods, equipments, motivation system etc.) Quality improvement must be divided between the two level

Juran Quality problems are rooting in insufficient and ineffective planning for quality In traditional way: Planning determine the tools for producing goods 20% of the operating process is waste, it is planned into the product or process Instead of quality improvement they only do quality control Juran trilogy Planning Control Improvement

Ishikawa Democratizing statistics: everyone is responsible for statistical analyzes, total involvement of the operating employees in improving quality Basic 7 tools of quality Process map – flow chart, step of process Check sheet – to collect errors for analyzes Histogram – graphic representation of data Scatter Diagrams – examine the relationship between variables (what cause the problem) Control Chart – is the process stable or not Cause-and-effect (Ishikawa) diagram – find all reason of the problem, directed tool for find all causes Pareto Chart – prioritize causes, determine problems must be focused on

Feigenbaum Father of Total Quality Control (TQC) the entire organization should be involved in quality improvement The quality is poor If the product is designed incorrectly (engineering) If the product is released in the wrong market If the customer relationship is not proper. (marketing) 3 steps of improvement 4 deadly diseases

Crosby Crosby’s four theorem Quality is the conformance to the requirements of customers. The whole system must be developed according to this approach. The main goal is zero-defect. Do the right product at the first time. Thus the applied method for quality assurance is prevention not control. Quality can be a source of profit. Quality costs must be evaluated, and on the basis of these costs, corrective actions should take place.

Taguchi Quality definitions: quality is measured in terms of loss to society if the service not performed as expected. Quality Loss Function (QLF): any deviation from target value results in loss to society Robust Design: products should be designed to be defect-free Concept design (technology and process choices) Parameter design (select parameters which have an effect on quality – amount of training, heights of a paper) Tolerance design (deals with decrease variation in order to fulfill the specification limits – use a higher-grade materials)

QLF (Qualtiy Loss Function) L=K*V2 K – constant, and V2- mean squared dviation from target value K=C/T2 C - unit repair cost T – tolerance interval LSL Target value USL

Exercise - QLF Suppose the cost to repair a radiator on an automobile is $200. Compute the QLF for losses incurred as a result of a deviation from target setting where a tolerance of 6±0,5 mm is required and the mean squared deviation from target is (1/6)2. Solution: K=200/0,52=800 L=K*V2=800*(1/6)2=$22,22/unit

TAGUCHI PROCESS 1. Problem identification 2. Brainstorming session identify factors, its settings, interactions, Control factor Noise factor Identify objectives The less is better Nominal is best The more is the better Experimental design Offline experimentation (number of replications) Experimentation Orthogonal array (determined by the number of factors and levels) Record the result Compute average performance for each factor Showing the best outcomes Analysis (which level of each factor is the proper one) Confirming experiment (validate results)

Contingency theory There are no schemes, firms do not have to use only one quality approach Successful firms adopt aspects of each approach that help them improve, understand them, and apply them creatively. It depends on the situation which approach is the best.

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