Manufacturing and Automation Systems: Techniques and by Cornelius T. Leondes PDF

By Cornelius T. Leondes

This selection of papers, aimed toward electric and electronics engineers - specifically these facing production and automatic platforms - covers contemporary advances within the box of recent keep watch over conception

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The difficulty in using the Volume-Variety Chart is the lack of specificity of what constitutes large volume, intermediate volume, and low volume. A number that constitutes a large volume production in one industry may become a low volume in another. A number commonly used as a break point for high volume is a million parts per year. This number is only a guide. Whereas the production of one million computer keyboards annually may constitute a large volume production, the production of one million resistors annually is, on the other hand, a low volume production.

The wide availability of IBM-PCs and compatibles has made this an attractive model for such systems. Embedded versions of the PC use memory to emulate disk drives, and have built-in interfaces for keyboards, displays, etc. This is all accomplished within a form factor and cost that is consistent with embedded applications. Use of such a system can potentially save on development equipment costs, but the embedded processor itself must be inexpensive enough to make that saving worthwhile. Testing of software for embedded systems presents yet another challenge.

Without the transferring function, machine starvation and blocking will occur. This will cause production to cease and consequently, product delivery dates will not be met. This important function notwithstanding, rarely is the material handling function considered by most practitioners in the preparation of production schedules. Most schedules focus only on machine capacity and with no consideration to the material handling system capacity. When the material handling system is undercapacitated relative to a production schedule, the net effect is long waiting times in outbound queues at work stations, long throughput time for jobs, increased work-in-process, and consequently, long production delays and missed delivery dates.

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