In today's extremely competitive manufacturing market, effective production planning and scheduling processes are critical to streamlining production and increasing profits. Success in these areas means increased efficiency, capacity utilization, and reduced time required to complete jobs. From the initial stages of plant location and capacity determination to plant operations and manpower scheduling, Production Planning and Industrial Scheduling, Second Edition presents a cohesive outlook on optimization and planning. The author provides a focus on practical applications and integrates logistics and planning in the areas of production and scheduling.
Critical Techniques for Optimizing Operational Productivity
Starting with the strategic development of plant locations and capacities, the book lays out a clear process for creating an effective production plan with considerations for existing production facilities. It discusses forecasting and aggregate planning, which can predict demands under scenarios. In addition, the book introduces techniques to improve plant efficiencies in various areas, as well as material requirement and inventory and capacity planning. This expanded second edition features new information on safety stock determination, uncertainty in demand, and resource center capacity planning. The problem-specific case studies illustrate the effect of different procedures on the entire system and stress coordination between independent techniques to help achieve optimal efficiency.
With the aid of this reference and the proper application of its concepts, industrial managers and engineers can reduce their manufacturing cost, succeed in fulfilling their customers' demands in a timely manner, and attain superior planning and overall control of manufacturing operations.
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Dileep R. Sule
A comprehensive reference for the broad range of problems encountered in the field, this second edition features new information on single machine scheduling, new procedures for common due dates, flowshop problems such as the n-job/m-machine problem, minimizing makespan with total penalty and multiple identical machines, batch scheduling for a limi
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