Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89757
Title: Setting planned lead times for a make-to-order production system with master schedule smoothing
Authors: Teo, Chee-Chong
Bhatnagar, Rohit
Graves, Stephen C.
Keywords: Production Smoothing
DRNTU::Engineering::Civil engineering
Make-to-order
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
http://hdl.handle.net/10220/48051
ISSN: 0740-817X
DOI: 10.1080/0740817X.2010.523765
Schools: Nanyang Business School 
School of Civil and Environmental Engineering 
Research Centres: Singapore-MIT Alliance Programme 
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
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