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|Title:||Setting planned lead times for a make-to-order production system with master schedule smoothing||Authors:||Teo, Chee-Chong
Graves, Stephen C.
|Issue Date:||2011||Source:||Teo, C.-C., Bhatnagar, R., & Graves, S. C. (2011). Setting planned lead times for a make-to-order production system with master schedule smoothing. IIE Transactions, 43(6), 399-414. doi:10.1080/0740817X.2010.523765||Series/Report no.:||IIE Transactions||Abstract:||This article considers a make-to-order manufacturing environment with fixed guaranteed delivery lead times and multiple product families, each with a stochastic demand process. The primary challenge in this environment is how to meet the quoted delivery times subject to fluctuating workload and capacity limits. The tactical planning parameters are considered, namely, the planning windows and planned lead times. The planning process that is modeled is the one in which the demand represents a dynamic input into the master production schedule. A planning window for each product family controls how the schedule of each product family is translated into a job release. It can be thought of as the slack that exists when the fixed quoted delivery lead time is longer than the total planned production lead time. Furthermore, the planned lead time of each station regulates the workflow within a multi-station shop. The model has underlying discrete time periods to allow the modeling of the planning process that is typically defined in time buckets; within each time period, the intra-period workflow that permits multiple job movements within the time period is modeled. The presented model characterizes key performance measures for the shop as functions of the planning windows and planned lead times. An optimization model is formulated that is able to determine the values of these planning parameters that minimize the relevant production-related costs.||URI:||https://hdl.handle.net/10356/89757
|ISSN:||0740-817X||DOI:||10.1080/0740817X.2010.523765||Rights:||© 2011 Institute of Industrial Engineers. All rights reserved. This paper was published by Taylor & Francis in IIE Transactions and is made available with permission of Institute of Industrial Engineers.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||CEE Journal Articles|
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