## Integrated production control systems: management, analysis, design, Volume 1Focuses 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. |

### From inside the book

Results 1-3 of 82

Page 266

Consider once again the example problem in which the EDD rule gave a

problem using the Wilkerson-Irwin algorithm. The resulting

-7-8-6, which ...

Consider once again the example problem in which the EDD rule gave a

**sequence**of 2-1-3-5-4-6-7-8. Figure 7.10 is a step-by-step solution of thisproblem using the Wilkerson-Irwin algorithm. The resulting

**sequence**is 2-1-3-4-5-7-8-6, which ...

Page 280

For K = 2 the corresponding

schedules are seen in Figure 7.21. Note that for K = 1 makespan was 36 hours

and for K = 2 the makespan was 33 hours. The

2-1-6-5-4.

For K = 2 the corresponding

**sequence**is 3-2-1-6-5-4. The resulting twoschedules are seen in Figure 7.21. Note that for K = 1 makespan was 36 hours

and for K = 2 the makespan was 33 hours. The

**sequence**to implement is thus 3-2-1-6-5-4.

Page 292

Using Data Set C,

time. Do this manually and with the SEQ.BAS program. Compare the results. 18.

Using Data Set C,

Using Data Set C,

**sequence**three parallel machines to minimize the mean flowtime. Do this manually and with the SEQ.BAS program. Compare the results. 18.

Using Data Set C,

**sequence**three parallel machines to reduce makespan.### What people are saying - Write a review

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### Contents

THE ROLE OF PRODUCTION CONTROL | 1 |

PRODUCTION CONTROL | 18 |

FORECASTING | 59 |

Copyright | |

14 other sections not shown

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### Common terms and phrases

ACTIM activity aggregate planning algorithm allow 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 economic order quantity Equation error example problem exponential smoothing factors follows forecasted demand function Gantt chart given in Figure historical data Industrial Engineering input inventory control inventory costs inventory items inventory level KANBAN lead-time line balancing linear linear model machine makespan manufacturing master schedule MATERIAL REQUIREMENTS PLANNING maximum mean flow mean tardiness minimize minimum MRP-II needed node operation optimal order costs order quantity output overtime parameters percent period personal computer PERT procedure processor production control RECPT regression analysis resource safety stock sequence shift shown in Figure solution step storage Tandem Computers technique total cost units variable vendor week