Abstract
![CDATA[Statistical process control is commonly used to methodically measure parameters of significance in product or process performance. However in one-off production or at low production rates it may take a considerable time before a statistically significant sample is collected, if useful data samples can be collected at all. In other situations, for example in monitoring product performance, logging low incidence indications may be used to forecast potential product failure. Often the knowledge of experienced people must be relied upon to supplement recorded data. It is argued that this knowledge requires some context to facilitate its effective utilization, and that this context must be its relation to a physical object or process, leading to some form of information map. Ultimately, the outcome is a decision to take some system improvement action. Three case examples are presented. A model of a system as four generic subsystems – a physical subsystem, an information subsystem, a decision subsystem and a knowledge subsystem is used to characterize three cases. The design of suitable mapping systems is discussed.]]
Original language | English |
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Title of host publication | ANZAM Operations Management Symposium 2005: Proceedings of the 3rd Annual Symposium of the Australian and New Zealand Academy of Management |
Publisher | Central Queensland University |
Number of pages | 6 |
ISBN (Print) | 1921047011 |
Publication status | Published - 2005 |
Event | ANZAM Operations Management Symposium - Duration: 1 Jan 2006 → … |
Conference
Conference | ANZAM Operations Management Symposium |
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Period | 1/01/06 → … |
Keywords
- process control
- statistical methods
- performance
- manufacturing industries
- case studies
- knowledge management