A STUDY ON CONTINUOUS QUALITY IMPROVEMENT STRATEGIES AND METHODS

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1 A STUDY ON CONTINUOUS QUALITY IMPROVEMENT STRATEGIES AND METHODS He Zhen Qi Ershi Liu Zixian Management School, Tianjin University Tianjin P. R. China Key Words: continuous quality improvement, quality function deployment, design of experiment, concurrent quality engineering, statistical process control. ABSTRACT How to continuously improve product and process quality has been a focus of research in quality management. A company that is going to set up its CAQ or establish an effective quality system should make sure that the CAQ or quality system will lead to continuous quality improvement so as to meet customer s growing demand for quality. Based on Juran s quality loop philosophy, the paper presents how to utilize continuous quality improvement tools in product design and manufacturing. It addresses the application of QFD and design of experiment to optimize product/process design and how to integrate quality tools. Based on the philosophy of concurrent quality engineering and successful experience of some world class businesses, the paper presents a continuous quality improvement flowchart and puts forward to the strategies to implement continuous quality improvement. 1. INTRODUCTION Facing with the fierce competition for high quality, many world class companies have implemented aggressive quality programs such as six sigma. As we know, six sigma is equivalent to less than 3.4 DPMO(defect per million opportunities) or PPM(Part Per Million)[1]. With the increase of customer s requirement for high quality, companies should strive to continuously improve the quality of their products or services. This is why some world class companies have changed their quality metrics from part per million to part per billion(ppb). Quality improvement is a never-ending process. On the contrary, one of the reasons for Chinese State-owned Enterprises to have lost competitiveness is that they don t have a Continuous Quality Improvement(CQI) system. Even though a lot of businesses have set up their quality management systems based on ISO9000, because ISO9000 does not focus on continuous improvement, their quality management systems can not guarantee continuously improve quality. The idea of continuous quality improvement is not new. Dr Edward Deming presented PDCA( Plan, Do, Check, Action) cycle for continuous improvement in 1950 s. Juran also developed quality loop to describe the process of continuous improvement in the life cycle of a product. For many manufacturing companies, how to implement the philosophy of CQI is a focus of research in recent years. With the implementation of computer integrated manufacturing systems(cims). It is possible to integrate quality tools to achieve CQI through marketing, product and process design, manufacturing etc. 2. CONTINUOUS QUALITY IMPROVEMENT THROUGH DESIGN Quality is the customers perception of the products they bought. The first stage of quality improvement is to have a clear understanding of customers wants and needs and to translate them 1

2 to product quality characteristics. Quality Function Deployment(QFD) is a method for structured product planning and development that enables a development team to specify clearly the customers wants and needs, and then to evaluate each product capability systematically in terms of its impact on meeting these needs. There are two dominant QFD models: Clausing s Four-Phase Model and the Matrix of Matrices [2]. These two models shared a lot in common and the most widely described and used is Four-Phase Model which consists of four phases: product planning(house of quality),design development(part deployment), process planning and production operations planning. During the first two phases it is very important to benchmark against competitors products. In the last two phases, robust design, FTA and FMEA should be integrated with QFD to design product/process parameters and set standard production operations. Fig. 1 gives the integration of quality tools during design cycle. Benchmarking Robust design/doe Process FMEA FTA&Product FMEA Phase 1 Phase 2 Phase 3 Phase 4 Product Planning Deployment Process Planning Production Operations Planning Fig 1. Quality tools integration in design cycle To achieve robust product/process design, of Experiment(DOE) is often used to study the relationship between the product/process quality characteristics(output responses) and input variables and select the appropriate level of controllable factors so that the product or the manufacturing process is insensitive to the variation of uncontrollable factors(noise factors). Genichi Taguchi developed his robust design philosophy and proposed Taguchi experimental method. Other experimental tools from the West(also called classical DOE), such as full factorial, fractional factorial and Response Surface Methodology(RSM) are also widely used in industries. From statistical and practical point of view, both Taguchi Method and classical DOE methods have their advantages and disadvantages[3]. They have different application conditions. Choosing appropriate DOE method should consider the objective of the experiment, number of input variables, the nature of the input variables(discrete or continuous), the maximum affordable experimental runs and curvature of the model.[4] 3. CONTINUOUS QUALITY IMPROVEMENT IN MANUFACTURING In manufacturing phase, continuous product quality improvement is achieved by process characterization and optimization. Fig. 2 provides a roadmap for process characterization and optimization. This roadmap starts with identification of quality issues through data analysis of CAQ(Computer Aided Quality) or some analytical tools such as Cause and Effect(Fishbone diagram). To leverage our resources, we should find out the quality bottleneck processes through Pareto charts or similar analysis. A cross-functional team is highly recommended for successful implementation of continuous quality improvement. To have a common understanding of the process the team should describe the process using process mapping. ANOVA or Multi-vari analysis 2

3 are powerful tools to find out if the process quality characteristic has single source of variation or multiple sources of variation so that we can reduce and control the variation using SPC tools. Quality Problem Identification/Fishbone, Scatter Plot, etc Prioritization to Determine Bottleneck/Pareto Chart Cross-functional team /Brainstorming Detailed Process mapping Determine Source of Variation/ANOVA, Multi Vari Analysis Measurement System Analysis Install New Measurement Systems Is it capable? Alternatives Exist? Process Capability Analysis Improve Measurement System Is it capable? Identification of Input Variables Determine SPC Plan Determine DOE Strategies Establish OCAP Factorial DOE or Taguchi Method Quality Data Collection Response Surface Methodology Process Parameters Optimization Determine Target Value and Tolerance Fig 2. Continuous quality improvement roadmap in manufacturing 3

4 Sometimes we often take it for granted that our measurement system is good but actually it is not. It is always safe to calculate the R&R(Repeatability and Reproducibility) of a measurement system see if it is less than 10% of the total process variation. If R&R% is more than 30%, a new measurement system should be used instead of the old one. If the measurement system is acceptable, a process capability analysis(cp and Cpk study )is conducted to see if it is capable. Different businesses may have different criteria for Cp and Cpk.. If the process is not capable, we can try to optimize it using experimental design. Control charts or other similar SPC tools is used keep the process in control after process is optimized and Out of Control Plan(OCAP) is developed for process control and adjustment. This roadmap is also an endless loop. After a quality bottleneck is resolved, a new quality issue may arise. 4. STRATEGIES FOR CONTINUOUS QUALITY IMPROVEMENT To successfully implement continuous quality improvement program, we strongly recommend the following strategies based on our consulting experience for several companies. 4.1 Management Commitment Like the implementation of ISO 9000, management commitment is everything for CQI. Management is responsible for setting goals, reviewing the progress, providing necessary resources and evaluating the result of CQI program. In Motorola, they have a ten times quality improvement goal for every 2 year. During weekly quality review, management requires engineers to show the quality measures such as Defect Per Unit(DPU) and see if it reaches the goal setting. 4.2 Concurrent Quality Engineering and Cross Functional Team Nearly 80% of quality problems can be traced to design. Concurrent development of product and process does not only reduce cycle time but also yield high quality. As we know Cp is tolerance divided by process spread, the efficient way to increase Cp is through the cooperation of design engineers and process engineers. A design engineer can give a reasonable design margin on condition that the process engineer tells him/her the width of the process spread. Other business functions such as equipment, quality assurance, production planning etc can give useful input to design team. This is why the design team is a cross-functional team. Customers and suppliers are also included in the design team because their inputs are critical to successful design. This can be illustrated by Fig. 3. SPC Customer Marketing Customers Marketing Needs Sales Suppliers Conceptua CE l Manufacturing Tolerance Process QFD FTA/FMEA Purchasing Manufacturing Process DOE Equipment Fig. 3 Continuous Quality Improvement Model 4 Planning

5 4.3 Total Employees Involvement The key of TQM is total employees involvement, so it is true to CQI. Everybody in a business has impact on quality directly or indirectly. Everybody s performance can be and must be measured by quality metrics. The suggestion system initiated by Japanese companies has been proven to be good way to motivate employees to participate quality improvement program. 5. CONCLUSIONS Successful implementation of CQI requires integration of various quality tools. The paper gives general guidelines on how to integrate quality tools to achieve continuous improvement. Some world class companies such as Motorola, GE, KODAK, Allied Signal are pushing Six Sigma Black Belt program to implement CQI. The objective of CQI is to meet the growing demand of customers and gain quality competitiveness. 5. ACKNOWLEDGEMENT The paper is financially supported by Chinese High-Technology Program(863). Grant No: REFERENCES 1. Fred R. Fadden, Six Sigma Quality Programs, Quality Progress, June, Lou Cohen, Quality Function Deployment: How to Make QFD Work for You, Addison-Wesley Publishing Company, He Zhen etc., A Comparative Study of Factorial DOE, RSM and Taguchi Method, Mechanical, No.11, D. C. Montgomery, and Analysis of Experiments, 4 th edition, John Wiley & Sons,1997 5

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