Imperial College London
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Paolo Taticchi, PhD, OMRI

Business School

Visiting Professor
 
 
 
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Contact

 

p.taticchi Website

 
 
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Location

 

Business School BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Tonelli:2013:10.1080/09537287.2011.609647,
author = {Tonelli, F and Paolucci, M and Anghinolfi, D and Taticchi, P},
doi = {10.1080/09537287.2011.609647},
journal = {Production Planning and Control},
pages = {110--127},
title = {Production planning of mixed-model assembly lines: A heuristic mixed integer programming based approach},
url = {http://dx.doi.org/10.1080/09537287.2011.609647},
volume = {24},
year = {2013}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Process technology capabilities are becoming increasingly important as flexible manufacturing continues to be more prevalent, and as competition compels companies to provide expanded variety, at ever lower cost, so introducing plant and processes technological constraints. Model flexibility can also benefit from an appropriate production planning process, especially concerning mixed-model assembly lines, since it can facilitate master scheduling and line balancing activities, which are essential aspects of flexibility. Robust and practical planning approaches have to take into account two different aspects: the first consists in ensuring that the elaborated aggregate plan can be disaggregated into at least one detailed feasible plan for the realised demand, whereas the second in ensuring that this detailed plan is feasible at the operational level. This article faces the model flexibility challenge, reviewing and discussing the planning problem of a real world assembly manufacturing system, producing high volume and a variety of agricultural tractors and machines, analysing and resolving some important issues related to technological, organisational and managerial constraints. This article illustrates the implementation of an Advanced Planning System integrated with a mixed integer-programming model, which is solved by a new iterative heuristic approach capable of achieving interesting planning improvements for model-flexibility management. © 2013 Copyright Taylor and Francis Group, LLC.
AU  - Tonelli,F
AU  - Paolucci,M
AU  - Anghinolfi,D
AU  - Taticchi,P
DO  - 10.1080/09537287.2011.609647
EP  - 127
PY  - 2013///
SN  - 0953-7287
SP  - 110
TI  - Production planning of mixed-model assembly lines: A heuristic mixed integer programming based approach
T2  - Production Planning and Control
UR  - http://dx.doi.org/10.1080/09537287.2011.609647
VL  - 24
ER  -
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