Use Of Statistical Process Control Research Articles

Improving maintenance quality using SPC tools

Examines the application and use of statistical process control (SPC) tools to improve the quality of maintenance work. Identifies areas in maintenance where SPC tools can be used. Gives an example that demonstrates the use of these tools in an integrated fashion and outlines the data needed to utilize these tools effectively. Finally, the need for an integration of the maintenance information system (MIS) and the quality information system (QIS) is highlighted.

The Use of Statistical Process Control in the Manufacture of High-Integrity Products

A study has been made of the use of statistical process control (SPC) in a company manufacturing high-integrity components for assembly into engines used in automobiles. The findings indicate that there is a lack of clear objectives for its use within the company. Some benefits have been achieved but the technique is being deployed imperfectly. A number of areas have been identified in which improvements are needed to make more effective use of SPC. For example, there is too much resetting of the machine tools, control limits are calculated too frequently, special causes have not been successfully identified and eliminated, teamwork is not widely used and insufficient resources are allocated to resolve problems in the company's manufacturing processes.

Statistical Process Control Charting Applied to the Analysis of Human Performance in Computer-Supported Environments

To develop usable Human-Machine Systems, we need Tools to evaluate and measure the length of learning periods, error rate, response time, and transfer of learning in the human operators of these systems (Whiteside, Bennett, and Holtzblatt, 1988). This research explores the use of Statistical Process Control (SPC) charts as a tool to visualize and analyze performance in a decision-making task. The data submitted to control charting was collected in an experiment that explored the effect of order of training or experience in working with alternate display formats. Results for an individual subject as well as a summary for one of the four experimental groups are discussed. Suggestions for further applications of these techniques are offered.

The Application of Group Technology Concept for Implementing SPC in Small Batch Manufacture

The use of Statistical Process Control (SPC) techniques for monitoring manufacturing processes in mass production is relatively easy. In small‐batch manufacture, however, such techniques can be difficult to implement due to lack of sufficient data to establish control decisions for control charts. Most of the early proposed solutions emphasized the product rather than the process, whereas many of the recently developed approaches favoured monitoring the process and not the product. All such approaches suggest the use of data transformation. The aim is to normalize the differences in the process mean and the variability for different components. Once an appropriate transformation is made, then sample data related to different components can be plotted on the same chart using sample statistics of the transformed data. An important part of transformation is the determination of process parameters for the component. Several methods for determining such parameters have already been suggested in the literature. Presents an alternative method for estimating the process parameters, based on the Group Technology (GT) concept. Generally speaking, the methodology consists of four steps, i.e. Classification and Coding (C&C), family formation, retrieving data, and estimating the process parameters. Discusses the characteristics of a C&C system for SPC and presents the details of its structure. Finally, based on the proposed structure, uses a flowchart to explain the procedure along with a practical application.

The use of statistical process control in batch processed PVC compounding. Part II

This paper describes various SPC methods that can be used to promote quality improvement, resulting in increased productivity and lower costs. By concentrating on preventative systems rather than detective systems, the operation has increased productivity by 5.0% over a period of two years with relatively little capital investment. This has resulted in an additional capacity of 650,000 kg per year.

The mathematics of success and failure (SPC)

The use of statistical process control (SPC) to improve quality is discussed. Mathematical tools and techniques for SPC are reviewed. How to decide when a change in an indicator is statistically significant is addressed. An approach to SPC in which one attempts to reduce process sensitivity to external variations rather than control these variations more tightly is discussed. >

Total Quality Management and its Application to F-14 Depot Maintenance

Understanding the concepts of quality costs through the reduction of waste and process variation is fundamental to the TQM philosophy. The evolution in U.S. quality control demands a shift from the traditional method of auditing the finished product and improving quality by fixing problems to a method of auditing processes. Likewise, TQM demands proper use of statistical process control and continuous training of management and the work force to ensure continuous improvement and productivity. This paper discusses how the Naval Aviation Depot (NADEP) Norfolk, Virginia, as an example of U.S. industry, employed the new management philosophy of TQM to reduce costs and boost productivity and efficiency. A specific application of TQM is highlighted with the preparation and implementation of the F-14 aircraft maintenance competition program. As part of this effort, the Norfolk depot's challenge was to streamline operations to minimize the cost of scheduled maintenance on a delivered F-14, while simultaneously maintaining quality. The competition against private industry for the aircraft workload provided unique opportunities to use TQM to make cultural changes throughout the depot. Norfolk would demonstrate that quality products are more a function of employee knowledge and interaction than the application of traditional quality control technology.

Statistical process control: An examination of some common queries

The authors, through a large-scale training programme and by carrying out a variety of quality-related research projects, have had extensive involvement with the introduction and use of Statistical Process Control (SPC) in Western European automotive suppliers. From these activities, the questions raised by organisations in their application and use of SPC have been noted and catalogued. This paper reports and examines the most frequent occurring questions.

The use of statistical process control in batch processed PVC compounding

AbstractThis paper describes the main Statistical Process Control (SPC) method that is being used by Canada Wire and Cable in the manufacture of their flexible PVC compounds. It outlines the benefits that are being realized by following a systematic approach towards using control charts. By employing SPC as a quality improvement tool, the operation has reduced its costs by an estimated $180,000 per year.

Minimizing Defects for a Silicon Nitride Deposition Process

Full factorial and Taguchi orthogonal arrays were used to characterize the silicon nitride low pressure chemical vapor deposition (LPCVD) process for film uniformity and particle density. Thickness and refractive index were measured using standard ellipsometric techniques. Particles were measured on patterned wafers using a Tencor Surfscan 7000 particle counter with pattern recognition capability. Both design methodologies produced identical results, with particles most dependent on total gas volume, and uniformity of the deposited film dependent on NH3:DCS (ammonia:dichlorosilane) gas ratio. Particle counts were minimized at both 4:1 and 6:1 NH3:DCS ratios and by reducing the total gas volume 10 percent, while uniformity continually improved as a 6:1 ratio was approached. It was learned that it is possible to choose an NH3:DCS gas ratio of 6:1 that simultaneously optimizes particles and film uniformity.The use of statistical process control (SPC) methods to improve process capability as measured by process capability (Cp) were employed to measure an overall increase in Cp from 1.1 to 1.5 for film uniformity. Implementation of the new process resulted in a 2.5-fold reduction in particle counts.

Technology Trends in Physical and Chemical Vapor Deposition Techniques

This paper reviews the present status and future needs of the thin film depositions-namely physical and chemical vapor depositions. The continuing shrinkage of the devices and circuits has placed demands not only on finding the new materials but more so on the technology of their application on such devices, circuits, and chips. After a brief review of the physical and vapor deposition technologies the changing needs are discussed including the emerging partially ionized beam technique. Effect of increasing wafer and die sizes and decreasing device dimensions, use of statistical process control and process simulations, emerging concepts of multiple process equipments and in-situ processing, and manufacturability are briefly discussed.

Statistical expert systems for process control and error detection for VLSI

As chip densities increase the number of process parameters which require attention increases dramatically making the job of the process engineer exceedingly difficult. This paper will discuss the use of Statistical Process Control and Taguchi-type statistically designed experiments to develop decision rules for use in statistical expert systems. Statistical experiments, using Taguchi's method, have been carried out in the area of photolithography. This results in a basis for decision rules indicating the importance and effect of a given sub-process in photolithography. Using the results of Taguchi experiments and expert process knowledge, an inference can be drawn to lead the expert system to a diagnostic conclusion. The statistical expert system incorporates, diagnosis, design, planning and scheduling.

Practical Implementation of Statistical Process Control in a Chemicals Industry

The implementation and use of statistical process control in a chemicals and plastics firm are examined. The essential external factors are focused upon, which are associated with the practical implementation of statistical process control. The important components of a Statistical Process Control process optimisation study are discussed in the context of their achievements at a manufacturing facility. Benefits achieved from a successful implementation of statistical process control are also discussed.

The role of SPC in printed circuit board manufacture

AbstractThis paper reports on research which examined the use of statistical process control (SPC) in the quality improvement process of a printed circuit board (PCB) manufacturer. The implementation of SPC is discussed along with the difficulties encountered and benefits achieved. The findings indicate that SPC is a tool which can be of considerable assistance in the quality improvement process of PCB manufacture. However, the variety of manufacturing technologies used and the number of interconnecting processes makes the application of SPC more difficult than in other traditional industries. The lessons learned include that the introduction of SPC must not be rushed, that discipline and support from all levels in the organization are crucial to its success, that SPC cannot be used in isolation—it needs the structure of a continuous improvement initiative, and that getting processes in a state of statistical control and capable, and keeping them there, is a difficult task which involves considerable effort and patience.

The application of statistical process control in U.K. automotive manufacture: Some research findings

AbstractThis paper reports on the findings of a questionnaire survey into the use of statistical process control (SPC) in a sample of United Kingdom automotive suppliers. All the 76 respondents had attended the Ford‐approved three‐day course on SPC held at the University of Manchester Institute of Science and Technology (UMIST). The survey investigated the following broad issues of SPC: motivation, implementation, application, suppliers and customers, and benefits. A number of findings surprised the authors; these included the number of organizations who had not appointed a SPC facilitator, organizations experiencing difficulties in deciding what type of control charts to use, control charts being ‘filled‐in’ by people not directly responsible for control of a process, charts being displayed away from work areas and the frankness of some suppliers in declaring that the vast majority of their manufacturing processes are not in a state of statistical control. If there is an overall message arising from the findings it is that the introduction and application of SPC should not be overcomplicated.

Monitoring, Targeting and the Use of Statistical Process Control within the Energy Profile of the Iron Founding Industry

The significance of energy within the manufacturing industry is identified and the relative energy costs are considered in terms of the process routes used. Energy requirements for the foundry industry are given as an example to highlight the consumption/cost relationship. The structure of energy management is presented with practical energy management experience discussed. Concepts of monitoring and targeting of energy are presented and the analysis of energy data is discussed, using SPC.

Improved quality of continuous flow manufacturing through the combination of statistical process control and conventional computer process control

This paper represents a portion of the evaluation of the use of Statistical Process Control within the realm of Conventional Computer Process Control. Various control charts commonly utilized in continuous processes are evaluated when subjected to process disturbances typical of continuous processes. The control charts considered are the Moving Average and Moving Range Chart combination, the Individual and Moving Range Chart combination, and the Exponentially Weighted moving Average Chart. The types of process disturbances considered are unit step and linear trend disturbances to the process average. The evaluation is based on the determination of the Average Run Lengths (ARLs) resulting from computer simulations.

The Way Forward from Statistical Process Control

It is proposed that the use of Statistical Process Control (SPC) in the UK is likely to follow one of three paths: — it will be used and management will await the next impetus from the Japanese before developing the techniques; — there will be a reaction against the changes inherent in implementing SPC, such that systems deteriorate and perhaps fade all together; — Britain could take the lead and develop the way forward in the pursuit of ever increasing quality. This article considers changes in the thinking, philosophy and strategy of quality that will have to take place for Britain to lead the way forward.