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. |
From inside the book
Results 1-3 of 55
Page 94
... week 1 is found by dividing 8 by 7 to get 1.14 . The seasonal indices can now be found by averaging the degrowthed data over the four weeks . Thus , in Table 3.11 , the seasonal index for Mondays is 1.20 ; that is , Mondays average out ...
... week 1 is found by dividing 8 by 7 to get 1.14 . The seasonal indices can now be found by averaging the degrowthed data over the four weeks . Thus , in Table 3.11 , the seasonal index for Mondays is 1.20 ; that is , Mondays average out ...
Page 95
... week 5 is 11.65 and Monday is 1.2 times the daily average , then Monday of week 5 should be 13.98 . Table 3.13 represents a two - week forecast by days for the examples problem , where fa is the daily seasonal index . Another good way ...
... week 5 is 11.65 and Monday is 1.2 times the daily average , then Monday of week 5 should be 13.98 . Table 3.13 represents a two - week forecast by days for the examples problem , where fa is the daily seasonal index . Another good way ...
Page 341
... week . Similarly , change 51 to your ( normal time −1 ) , and so on until you get to your crash time . Disregard unused weeks in the above schedule . 25. Use the CPM.BAS program to determine the critical path ( s ) for the network ...
... week . Similarly , change 51 to your ( normal time −1 ) , and so on until you get to your crash time . Disregard unused weeks in the above schedule . 25. Use the CPM.BAS program to determine the critical path ( s ) for the network ...
Contents
THE ROLE OF PRODUCTION CONTROL | 1 |
PRODUCTION CONTROL | 18 |
FORECASTING | 59 |
Copyright | |
14 other sections not shown
Other editions - View all
Common terms and phrases
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