Statistical Process Control and Design of Experiment Process Improvement Methods for the Powertrain Laboratory

2003 ◽  
Author(s):  
Todd Dvorak ◽  
Linda Malone ◽  
Robert Hoekstra
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Process Improvement ◽  
Design Of Experiment ◽  
Statistical Process

Statistical Process Control for Process Improvement in Industry: A Case Study

2015 ◽  
Vol 21 (5) ◽  
pp. 1094-1098
Author(s):  
Sin Yin Teh ◽  
Heng Chin Low ◽  
Ping Chow Teoh
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Process Improvement ◽  
Statistical Process

scholarly journals QUALITY ENGINEERING TRANSFORMATION OVER THE YEARS AND ISSUES - A REVIEW

2021 ◽  
Vol 5 (10) ◽  
Author(s):  
Pappu Rama Subramaniam ◽  
Pappu Rama Subramaniam
Keyword(s):  
Quality Management ◽  
Process Control ◽  
Statistical Process Control ◽  
Design Of Experiment ◽  
Quality Function Deployment ◽  
Quality Engineering ◽  
Quality Model ◽  
Statistical Process ◽  
Quality Function ◽  
Goods And Services

Traditional quality management and monitoring has been shown to be unsuccessful. Today, emerging companies are vying for more value to the consumer in order to ensure their maximum success and sustainability. Many businesses want to ensure that their goods and services are of high quality in order to attract customers. The current situation is implementing quality engineering solutions in industries. Quality engineering is the method of evaluating, handling, designing, and maintaining various systems in compliance with high standards. This method ensures that each stage of the product development cycle is subjected to a thorough inspection by quality engineers, reducing possible losses by eliminating defects from the start. Furthermore, highquality maintenance is important and should be made available for a long time after the product has been shipped. Customers' preferences are shifting significantly, necessitating improvements in design and production technology, which is becoming increasingly critical in satisfying individual customers. This necessitates paying particular attention to quality engineering. The paper starts with a review on quality emphasis over the last 37 years, quality concepts, and quality model evolution followed by i) a contrast of quality management and quality engineering, ii) developments in quality engineering tools and techniques, such as statistical process control (SPC), design of experiment (DoE), Taguchi processes, and quality function (QFD). This paper also looks at quality engineering-related problems. There are brief reviews of recent developments in well-known quality tools, such as statistical process control, quality function deployment, and design of experiment. The aim of this paper is to place quality engineering in context and emphasise its significance, as well as to present some issues at the frontiers of quality engineering.

Improving Process Capability of Cutting and Drilling Processes of Elevator Assembly Parts

2019 ◽  
Vol 950 ◽  
pp. 90-94
Author(s):  
Rapee Kanchana
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Process Improvement ◽  
Manufacturing Process ◽  
Process Capability ◽  
Small Enterprise ◽  
Fixture Design ◽  
Drilling Process ◽  
Statistical Process ◽  
Root Cause

Statistical process control (SPC) technique has become more and more often used for manufacturing process improvement with understanding the process and detecting the process variation. This paper presents a study from a small enterprise classified as OEM supply elevator assembly parts. A process capability study is performed for cutting and drilling processes in order to verify the process capable of consistently meeting the required specification and delivering quality products since increasing a number of rework parts. Why-why analysis was used to identify the root cause and the principles of Poka Yoke and jig & fixture design were then applied by design a measure gauge for cutting and drilling processes. After improvement, the result shows that the Cpk of cutting process increase from 0.19 to 2.72 while Cpk of drilling process also increase from 0.36 to 4.50. Since the Cpk is greater than 1.3 this means that both two processes have a capable to produce the output meet specification.

scholarly journals Statistical process control part 2: using statistical process control to measure process improvement in patient flow

2009 ◽  
Vol 33 (3) ◽  
pp. 412 ◽  
Author(s):  
Tamara G Chetter
Keyword(s):  
Health Care ◽  
Quality Improvement ◽  
Process Control ◽  
Statistical Process Control ◽  
Process Improvement ◽  
Patient Flow ◽  
Care Process ◽  
Statistical Process ◽  
The Impact ◽  
Control Part

THE FIRST ARTICLE in this series, ?Statistical process control part 1: a primer for using statistical process control in health care process improvement? 1 (in this issue of the Journal), introduced the basic concepts of statistical process control (SPC) and its main tool, the control chart. While this set of techniques was originally developed in the manufacturing sector, there is growing realisation in recent years that SPC (and also other quality improvement techniques, such as Six Sigma and lean thinking) can be successfully applied to health care quality improvement.2 The reason for this is that SPC is a potent and powerful, yet simple tool for tracking, and detecting any variation in, process performance over time; which creates the opportunity for health professionals to promptly respond to any improvement or deterioration in the process. Perhaps the most valuable feature of SPC techniques however, is the ability to place a change in the outcome of a process in close temporal proximity to the redesign and improvement of the process. This means SPC can reliably evaluate the effectiveness of quality improvement initiatives implemented at the front line of health service delivery, despite the complexities of the hospital system and the challenges this often poses for health services research (for example, the inability to use robust research designs). The purpose of this companion article is to therefore demonstrate the practical application of SPC in a health care organisation. Specifically, the technique of control charting was used to track the impact of patient flow process improvement interventions in a public hospital, in the hope that this will exemplify to health care professionals the value and simplicity in applying SPC as part of their daily work.

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