Optimization of Scheduling For Small Batch and Customized Mixed-Model Assembly Production

DOI

10.2991/mse-17.2017.22How to use a DOI?

Keywords

Small batch and customization, mixed-model assembly, scheduling, lean production, intelligent algorithm

Abstract

In order to solve the complex problem of small batch and customized mixed-model assembly production (SBC-MAP) that lack of optimization scheduling, a optimization scheduling model and algorithm was studied by integrating the methods of math, management technology, information technology and a heuristic algorithm. Market fast response and balanced production were proposed as the target combining with market demand and production characteristics. The variation coefficient of delivery date and dispersion coefficient of balanced production were taken as the key performance indicator (KPI), and bottleneck materials and throughput were considered as the constraint. Eventually, the model of multiple objective and multiple constraint of scheduling optimization was constructed to realize the lean manufacturing goals. Meantime, to effectively solve the scheduling problem of fast and accurate, intelligent optimization algorithm was devised. The algorithm integrated online data acquisition, automatic Merge Sort (MS) and Adaptive Equalization (AE) algorithm, and search quality and efficiency were improved. Through practical application in agricultural machinery products showed the effectiveness and feasibility of the proposed model and algorithm.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiao-Ying Yang
AU  - Lin-Ming Xu
AU  - Yu-Zhe Wang
PY  - 2017/10
DA  - 2017/10
TI  - Optimization of Scheduling For Small Batch and Customized Mixed-Model Assembly Production
BT  - Proceedings of the 3rd Annual 2017 International Conference on Management Science and Engineering (MSE 2017)
PB  - Atlantis Press
SP  - 83
EP  - 89
SN  - 2352-5428
UR  - https://doi.org/10.2991/mse-17.2017.22
DO  - 10.2991/mse-17.2017.22
ID  - Yang2017/10
ER  -