Procedure for reducing the risk of delayed deliveries in make-to-order production

Make-to-order production is generally operated in a very unpredictable and competitive environment, where the key factors to succeed are to provide high service levels and flexibility while at the same time offering inexpensive products. To receive customers, production companies must often promise...

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Published inProduction planning & control Vol. 20; no. 4; pp. 332 - 342
Main Authors Stefansson, H., Jensson, P., Shah, N.
Format Journal Article
LanguageEnglish
Published London Taylor & Francis Group 01.06.2009
Taylor & Francis LLC
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ISSN0953-7287
1366-5871
DOI10.1080/09537280902843698

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Abstract Make-to-order production is generally operated in a very unpredictable and competitive environment, where the key factors to succeed are to provide high service levels and flexibility while at the same time offering inexpensive products. To receive customers, production companies must often promise short lead-times and the option of adjustable order quantities and delivery dates. Coping with uncertainty and variable demand is a challenging task. With the additional challenge of cutting down the production costs to be able to provide inexpensive products, proper planning and scheduling of the production becomes very difficult and crucial for success. It is therefore of crucial importance to develop systematic methods to address the problem of planning and scheduling under uncertainty in order to create efficient and reliable plans and thereby reduce the risk of delayed deliveries of customer orders. This study introduces the subject of creating robust production plans and schedules in the typical modern production environment characterised by several important sources of uncertainty. We introduce an efficient and practical modelling approach for creating robust production plans under uncertain and varying demand conditions. As an inspiration we have a large real-world problem originating from a complex pharmaceutical enterprise.
AbstractList Make-to-order production is generally operated in a very unpredictable and competitive environment, where the key factors to succeed are to provide high service levels and flexibility while at the same time offering inexpensive products. To receive customers, production companies must often promise short lead-times and the option of adjustable order quantities and delivery dates. Coping with uncertainty and variable demand is a challenging task. With the additional challenge of cutting down the production costs to be able to provide inexpensive products, proper planning and scheduling of the production becomes very difficult and crucial for success. It is therefore of crucial importance to develop systematic methods to address the problem of planning and scheduling under uncertainty in order to create efficient and reliable plans and thereby reduce the risk of delayed deliveries of customer orders. This study introduces the subject of creating robust production plans and schedules in the typical modern production environment characterised by several important sources of uncertainty. We introduce an efficient and practical modelling approach for creating robust production plans under uncertain and varying demand conditions. As an inspiration we have a large real-world problem originating from a complex pharmaceutical enterprise.
Make-to-order production is generally operated in a very unpredictable and competitive environment, where the key factors to succeed are to provide high service levels and flexibility while at the same time offering inexpensive products. To receive customers, production companies must often promise short lead-times and the option of adjustable order quantities and delivery dates. Coping with uncertainty and variable demand is a challenging task. With the additional challenge of cutting down the production costs to be able to provide inexpensive products, proper planning and scheduling of the production becomes very difficult and crucial for success. It is therefore of crucial importance to develop systematic methods to address the problem of planning and scheduling under uncertainty in order to create efficient and reliable plans and thereby reduce the risk of delayed deliveries of customer orders. This study introduces the subject of creating robust production plans and schedules in the typical modern production environment characterised by several important sources of uncertainty. We introduce an efficient and practical modelling approach for creating robust production plans under uncertain and varying demand conditions. As an inspiration we have a large real-world problem originating from a complex pharmaceutical enterprise. [PUBLICATION ABSTRACT]
Author Stefansson, H.
Jensson, P.
Shah, N.
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Cites_doi 10.1063/1.2715540
10.1016/S0098-1354(03)00050-4
10.1016/0098-1354(95)00141-N
10.1016/j.compchemeng.2003.09.008
10.1021/ie960470v
10.1016/j.ejor.2006.06.011
10.1016/j.compchemeng.2005.02.023
10.1002/aic.10989
10.1021/ie0007724
10.1016/j.compchemeng.2003.09.020
10.1016/j.compchemeng.2006.05.035
10.1007/s00291-002-0101-7
10.1016/j.compchemeng.2006.02.008
10.1021/ie970927g
10.1016/S0305-0483(99)00080-8
10.1016/j.cor.2006.02.011
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References Bertsimas D (CIT0002) 2007; 101
CIT0010
CIT0021
Stefansson H (CIT0020) 2006
CIT0011
CIT0022
Mendez CA (CIT0015) 2001; 31
Bassett MH (CIT0001) 1997; 36
Bodington EC (CIT0004) 1995
Stefansson H (CIT0019) 2005
Dedopoulos IT (CIT0005) 1995; 19
Dogan ED (CIT0006) 2005
Mendez CA (CIT0013) 2004; 28
CIT0003
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Shah N (CIT0017) 1999; 320
CIT0016
Ierapetritou MG (CIT0007) 1998; 37
CIT0018
CIT0009
CIT0008
Mendez CA (CIT0012) 2003; 27
References_xml – volume: 101
  start-page: 7
  issue: 7
  year: 2007
  ident: CIT0002
  publication-title: Journal of Applied Physics
  doi: 10.1063/1.2715540
– volume-title: Planning, scheduling and control: integration in the process industries
  year: 1995
  ident: CIT0004
– volume: 27
  start-page: 1247
  issue: 8
  year: 2003
  ident: CIT0012
  publication-title: Computers & Chemical Engineering
  doi: 10.1016/S0098-1354(03)00050-4
– volume: 19
  start-page: S693
  year: 1995
  ident: CIT0005
  publication-title: Computers & Chemical Engineering
  doi: 10.1016/0098-1354(95)00141-N
– volume: 28
  start-page: 1059
  issue: 6
  year: 2004
  ident: CIT0013
  publication-title: Computers & Chemical Engineering
  doi: 10.1016/j.compchemeng.2003.09.008
– volume: 36
  start-page: 1717
  issue: 5
  year: 1997
  ident: CIT0001
  publication-title: Industrial & Engineering Chemistry Research
  doi: 10.1021/ie960470v
– ident: CIT0010
  doi: 10.1016/j.ejor.2006.06.011
– volume: 320
  start-page: 75
  issue: 94
  year: 1999
  ident: CIT0017
  publication-title: AIChE Symposium Series
– volume-title: A decomposition method for the simultaneous planning and scheduling of single stage continuous multiproduct plants
  year: 2005
  ident: CIT0006
– ident: CIT0018
  doi: 10.1016/j.compchemeng.2005.02.023
– volume-title: European symposium on computer aided process engineering – 15
  year: 2005
  ident: CIT0019
– ident: CIT0021
  doi: 10.1002/aic.10989
– volume-title: 16th European symposium on computer aided process engineering and 9th international symposium on process systems engineering
  year: 2006
  ident: CIT0020
– ident: CIT0022
  doi: 10.1021/ie0007724
– ident: CIT0011
  doi: 10.1016/j.compchemeng.2003.09.020
– ident: CIT0008
  doi: 10.1016/j.compchemeng.2006.05.035
– ident: CIT0009
  doi: 10.1007/s00291-002-0101-7
– ident: CIT0014
  doi: 10.1016/j.compchemeng.2006.02.008
– volume: 37
  start-page: 4341
  issue: 11
  year: 1998
  ident: CIT0007
  publication-title: Industrial & Engineering Chemistry Research
  doi: 10.1021/ie970927g
– ident: CIT0016
  doi: 10.1016/S0305-0483(99)00080-8
– ident: CIT0003
  doi: 10.1016/j.cor.2006.02.011
– volume: 31
  start-page: 455
  issue: 5
  year: 2001
  ident: CIT0015
  publication-title: Latin American Applied Research
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StartPage 332
SubjectTerms optimisation
Order quantity
Pharmaceutical industry
planning
production
Production planning
risk
robust
scheduling
Studies
Uncertainty
Title Procedure for reducing the risk of delayed deliveries in make-to-order production
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