Edelson, Norman; Ellis, Melinda; Kharkar, Anil, Ph.D.; Stutts, Brian, Ph.D. (1992, ASQC) Corning Incorporated, Corning, New York
Some manufacturing operations often seem chaotic because they are plagued with seemingly complex problems. Common solutions, such as SPC and designed experiments, can fail to eliminate this chaos due to changes in process variability, among other things. In this paper, a sequential three phase strategy that eliminates these problems is presented. Phase One of the strategy focuses on improving consistency of inputs to the process. In Phase Two, the process is brought into statistical control. During Phase Three, the process capability is improved as needed. This strategy is unique in that it requires process stabilization prior to experimentation of equipment upgrades. The three phase strategy was developed through analysis of projects carried out by a staff engineering group. Characteristics of efficient and successful programs were examined. The methods of the most successful and efficient are essentially captured in the Sequential Three Phase Process Improvement Strategy, and embodied in more detail in the Manufacturing Process Improvement Flow Chart. A large number of specific techniques were also identified while reviewing available literature and actual case histories. This knowledge base was compiled into a Process Engineering Manual. A complex three day training simulation--the Manufacturing Process Improvement Workshop--was developed to demonstrate how and why the strategy works. The workshop puts participants into a problem situation in a plant and shows them how the problem can be corrected. by following the flow chart and the strategy. A case study of a typical successful application resulted in a process being taken from a yield and up time under 40% to a consistent 95% level over the course of a year.
Capability study,Case study,Flowcharts,Manufacturing,Process control,Process improvement,Statistical process control (SPC),Variation