Do Flexibility and Chaining Really Help? An Empirical Analysis of Automotive Plant Networks

V. Choudhary, Sameer Hasija, Serguei Netessine
{"title":"Do Flexibility and Chaining Really Help? An Empirical Analysis of Automotive Plant Networks","authors":"V. Choudhary, Sameer Hasija, Serguei Netessine","doi":"10.2139/ssrn.3301302","DOIUrl":null,"url":null,"abstract":"We study production networks of automotive assembly plants to shed new light on the impact of flexibility on plant productivity. We observe that the contemporary manufacturing networks of automotive assembly plants of three US companies (Chrysler, Ford and General Motors) have become less flexible over the years despite the reported benefits of flexibility. To understand this phenomenon, we utilize flexibility indices that have been developed in the modeling literature to measure flexibility but have never been tested in an empirical setting. We identify shortcomings in existing indices and propose a new index to measure network flexibility. Using our proposed index, we find that both extremes of flexibility (too much or too little) affect productivity negatively. Therefore, intermediate levels of flexibility are optimal because they balance the trade-off between better matching of supply and demand with excessive downtime due to model changeovers (changing production from one model to another), which were not accounted for in the modeling literature. Using plant-level production schedules, we find that productivity losses due to changeovers have a significant negative effect on manufacturing productivity, often making celebrated “chaining” approaches to network configuration uneconomical. Counterintuitively, firms can often benefit by reducing flexibility levels, depending on the current level of flexibility in the manufacturing network. For example, our estimates indicate that a firm with a highly flexible production network can gain up to 8.8% in productivity by rearranging its network. This can result in an average savings of 460,000 labor-hours in a plant with an average production of 200,000 vehicles per year. Using simulation, we show that well-established long-chain configurations cease to perform better than sparser configurations when changeover losses are accounted for, indicating that firms can be better-off by adopting a sparser structure than chaining to improve productivity.","PeriodicalId":12584,"journal":{"name":"Global Commodity Issues eJournal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Commodity Issues eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3301302","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

We study production networks of automotive assembly plants to shed new light on the impact of flexibility on plant productivity. We observe that the contemporary manufacturing networks of automotive assembly plants of three US companies (Chrysler, Ford and General Motors) have become less flexible over the years despite the reported benefits of flexibility. To understand this phenomenon, we utilize flexibility indices that have been developed in the modeling literature to measure flexibility but have never been tested in an empirical setting. We identify shortcomings in existing indices and propose a new index to measure network flexibility. Using our proposed index, we find that both extremes of flexibility (too much or too little) affect productivity negatively. Therefore, intermediate levels of flexibility are optimal because they balance the trade-off between better matching of supply and demand with excessive downtime due to model changeovers (changing production from one model to another), which were not accounted for in the modeling literature. Using plant-level production schedules, we find that productivity losses due to changeovers have a significant negative effect on manufacturing productivity, often making celebrated “chaining” approaches to network configuration uneconomical. Counterintuitively, firms can often benefit by reducing flexibility levels, depending on the current level of flexibility in the manufacturing network. For example, our estimates indicate that a firm with a highly flexible production network can gain up to 8.8% in productivity by rearranging its network. This can result in an average savings of 460,000 labor-hours in a plant with an average production of 200,000 vehicles per year. Using simulation, we show that well-established long-chain configurations cease to perform better than sparser configurations when changeover losses are accounted for, indicating that firms can be better-off by adopting a sparser structure than chaining to improve productivity.
灵活性和连锁真的有用吗?汽车工厂网络的实证分析
我们研究了汽车装配厂的生产网络,以揭示柔性对工厂生产率的影响。我们观察到,三家美国公司(克莱斯勒(Chrysler)、福特(Ford)和通用汽车(General Motors))的当代汽车装配厂制造网络多年来变得不那么灵活,尽管有报道称灵活性带来了好处。为了理解这一现象,我们利用在建模文献中开发的灵活性指数来测量灵活性,但从未在实证环境中进行过测试。我们发现了现有指标的不足,并提出了一个新的指标来衡量网络的灵活性。使用我们提出的指数,我们发现两个极端的灵活性(太多或太少)都会对生产力产生负面影响。因此,中间水平的灵活性是最优的,因为它们平衡了由于模型转换(将生产从一种模型更改为另一种模型)而导致的供应和需求的更好匹配与过度停机之间的权衡,建模文献中没有考虑到这一点。使用工厂级生产计划,我们发现由于转换造成的生产率损失对制造生产率有显著的负面影响,通常使著名的“连锁”网络配置方法不经济。与直觉相反,企业通常可以通过降低灵活性水平而受益,这取决于制造网络当前的灵活性水平。例如,我们的估计表明,具有高度灵活的生产网络的企业通过重新安排其网络可以获得高达8.8%的生产率。在一个平均每年生产20万辆汽车的工厂,这可以平均节省46万小时的劳动时间。通过模拟,我们表明,当考虑到转换损失时,完善的长链结构不再比稀疏的结构表现得更好,这表明企业可以通过采用比链式结构更好的结构来提高生产率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信