## Integrated production control systems: management, analysis, 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. |

### From inside the book

Results 1-3 of 39

Page 120

management, analysis, design David D. Bedworth, James Edward Bailey ... The

additional coefficients are found through

,t) sin — + (C, + D,f ) cos — + (A2 + B2t) sin — Pi Pi Pi + (C2 + D2t) cos — Pi ...

management, analysis, design David D. Bedworth, James Edward Bailey ... The

additional coefficients are found through

**regression analysis**forming: f(t) = (A, + B,t) sin — + (C, + D,f ) cos — + (A2 + B2t) sin — Pi Pi Pi + (C2 + D2t) cos — Pi ...

Page 131

management, analysis, design David D. Bedworth, James Edward Bailey. 4.

Consider the following set of basically constant-model data. Fit this data with both

a linear and a constant

can ...

management, analysis, design David D. Bedworth, James Edward Bailey. 4.

Consider the following set of basically constant-model data. Fit this data with both

a linear and a constant

**regression model**to demonstrate that the linear modelcan ...

Page 146

normally distributed random variables. Limiting oneself to quantitative factors is a

problem. Managers often consider factors that cannot easily be measured. A

company ...

**regression analysis**assumptions, the factors should also be independentnormally distributed random variables. Limiting oneself to quantitative factors is a

problem. Managers often consider factors that cannot easily be measured. A

company ...

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### Contents

THE ROLE OF PRODUCTION CONTROL | 1 |

PRODUCTION CONTROL INFORMATION FLOW | 16 |

PROJECT PLANNING | 41 |

Copyright | |

11 other sections not shown

### Common terms and phrases

ACTIM activity aggregate planning Algorithm analysis approach Arizona State University assigned assumed average batch Box-Jenkins calculated CARD chapter coefficients CONNON considered Crash critical path cycle cyclic Data Set determine developed due date economic order quantity Equation error evaluate example problem exponential smoothing forecasted demand FORNAT Gantt chart given in Figure given in Table graphical heuristic Industrial Engineering input inventory control inventory costs inventory item inventory level iterative lead-time Line Balancing linear makespan manufacturing master schedule materials materials requirement plan mean flow-time mean tardiness minimize minimum needed node normal operation optimal optimum order quantity overtime period PERT PREDICTS PRINT procedure processor production control regression regression analysis resource rule safety stock sequence solution station step storage tardy tasks techniques time-series time-series analysis TIMRES TINE total cost units URITE utilized week