Integrated Production, Control Systems: Management, Analysis, and DesignFocuses on the quantitative approaches necessary to computer-integrated manufacturing systems, and integrates major topics covering all phases of the production control cycle: production information processing and flow, production planning, forecasting, material requirements planning and monetary control, and scheduling. This new edition features a compendium set of 11 user-friendly computer programs for the IBM PC that enhance the teaching power of the text, allowing readers to solve real-life problems. Among programs included are growth forecasting, aggregate planning, material requirements planning, lot sizing and inventory control, and limited-resource scheduling. The chapters on scheduling give particularly thorough coverage on this difficult subject. Solutions are clearly presented, with many examples and exercises included in the text. |
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Page 159
... Data Set A with the added restriction that inventory in any period should not fall below 10 , 50 , or 80 units . Discuss the effect of this added constraint . 12. Do problem 5 for Data Set B with the added restriction involving initial ...
... Data Set A with the added restriction that inventory in any period should not fall below 10 , 50 , or 80 units . Discuss the effect of this added constraint . 12. Do problem 5 for Data Set B with the added restriction involving initial ...
Page 291
... Data Set A , develop the minimum mean unweighted flow - time schedule for one processor . What is the minimum mean flow time ? 2. Using Data Set A , develop the single - processor minimum - weighted mean flow - time schedule . What is ...
... Data Set A , develop the minimum mean unweighted flow - time schedule for one processor . What is the minimum mean flow time ? 2. Using Data Set A , develop the single - processor minimum - weighted mean flow - time schedule . What is ...
Page 419
... implement Algorithm 10.1 and test it using Data Sets A through F. 7. Using Algorithm 10.2 , determine a schedule for staffing Data Set A. Is the schedule optimal ? 8. Do problem 7 for Data Set B. 9. Do 10.8 EXERCISES 419 Exercises.
... implement Algorithm 10.1 and test it using Data Sets A through F. 7. Using Algorithm 10.2 , determine a schedule for staffing Data Set A. Is the schedule optimal ? 8. Do problem 7 for Data Set B. 9. Do 10.8 EXERCISES 419 Exercises.
Contents
THE ROLE OF PRODUCTION CONTROL | 1 |
PRODUCTION CONTROL | 18 |
FORECASTING | 59 |
Copyright | |
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ACTIM activity aggregate planning algorithm allow analysis approach assembly assigned assumed BASICA batch BEGIN INVENTORY Box-Jenkins calculate carrying costs Chapter completion component considered constraints critical path cycle Data Set determine due date Equation error example problem exponential smoothing factors follows forecasted demand function function key Gantt chart given in Figure GROSS REQUIREMENTS Industrial Engineering input inventory costs inventory item inventory level KANBAN Line Balancing line-of-balance linear linear model machine makespan manufacturing master schedule MATERIAL REQUIREMENTS PLANNING maximum mean tardiness minimize minimum needed node operation optimal order costs order quantity output overtime parameters percent period personal computer procedure processor production control purchase quadratic RECPT regression regression analysis resource safety stock sequence shift shown in Figure solution step storage Tandem Computers technique total cost units values vendor week