有能力的资源和拥塞的生产计划

IF 6.1 3区 管理学 Q1 ENGINEERING, INDUSTRIAL Production Planning & Control Pub Date : 2021-07-26 DOI:10.1080/09537287.2021.1953721
C. Roser
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The subsequent chapters look deeper at clearing functions, with chapter 7 on univariate clearing functions, chapter 8 on multivariate clearing functions, chapter 9 on lot sizing in clearing functions, and chapter 10 on application of clearing functions before the final chapter 11 concludes the book. Overall, this book by the two authors who are well known in this field is a very thorough and extensive literature review of the existing research on production planning. It includes hundreds of references up to 2019. The aim of the book is to give a structured overview of existing research. In the authors own words, they want to ‘[... raise] more questions in the mind of the reader than [to answer ... ]’ (pg. 276). The target audience are academic researchers focussing on the field of production planning. The book is far up in the ivory tower, and has few uses for practitioners, either due to the limitations and assumptions of the models, or due to the mathematical complexity exceeding the ability of the average production professional. Even for academics it is a tough read, and most readers will likely focus on selected topics of the book rather than reading it cover to cover. Hence, it is not a large problem that the different sections are not well-integrated. For example, the mathematical nomenclature is not consistent even within chapters, and usually uses the variables as found in the source references. Some variables would also benefit from a more concise explanation or definition. Similar applies to the figures, which also frequently originate from the references and have vastly different styles. Other figures that seem original to the book lack rigour. The differentiation using colours will be lost in greyscale printing, lines are sometimes not straight, and text in figures is misaligned. In combination, this gives some illustrations and equations an unfinished appearance. It is a bit more problematic that the wording is also not consistent. For example, the lead time is often but not always called ‘cycle time’—which in industry often has a very different meaning than lead time. Variability and variance also seem to be sometimes used interchangeably. The book is also focussed very much on make-to-order production—admittedly the more difficult production planning topic—but is rather thin on make-to-stock related problems. The book focuses on lead time, which would be a less relevant KPI for make-to-stock production. Some other highly related topics like pull production and kanban get barely a passing mention. A few chapters include critical views, but most chapters leave it up to the reader to decide which method is most applicable. 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引用次数: 1

摘要

这本书给出了与生产计划有关的研究的全面和广泛的概述。这是一个重要的工业问题,因为生产计划的主题在实践中仍然有很多需要改进的地方。特别是对于作业车间,生产计划被认为是困难的,导致许多低效率和不满意的生产性能。本书的前三章作为概述和介绍,其中第一章介绍了问题,第二章定义了一些相关的KPI,第三章概述了不同的生产计划框架。这本书然后开始深入到生产计划的不同框架。第4章侧重于工作量控制领域,第5章讨论假设固定交货时间的模型,第6章讨论时变交货时间的模型。随后的章节更深入地探讨清算函数,第7章讨论单变量清算函数,第8章讨论多变量清算函数,第9章讨论清算函数中的批量大小,第10章讨论清算函数的应用,最后的第11章结束本书。总的来说,这两位在该领域非常知名的作者所著的这本书对现有的生产计划研究进行了非常全面和广泛的文献回顾。它包括截至2019年的数百篇参考文献。这本书的目的是给现有的研究一个结构化的概述。用作者自己的话来说,他们想要“……在读者心中提出更多的问题,而不是回答……(第276页)。目标读者是专注于生产计划领域的学术研究人员。由于模型的限制和假设,或者由于数学的复杂性超出了一般生产专业人员的能力,这本书在象牙塔上很远,对实践者几乎没有用处。即使对学者来说,这也是一本很难读的书,大多数读者可能会专注于书中的选定主题,而不是从头到尾读一遍。因此,不同的部分没有很好地整合并不是一个大问题。例如,即使在章节中,数学命名法也不一致,并且通常使用源引用中找到的变量。一些变量也将受益于更简洁的解释或定义。类似的情况也适用于图形,这些图形也经常来源于参考文献,并且具有截然不同的风格。书中其他看似原创的人物形象缺乏严谨。在灰阶印刷中,使用颜色的区别会丢失,线条有时不直,图形中的文本不对齐。结合起来,这给了一些插图和方程一个未完成的外观。更有问题的是,措辞也不一致。例如,交货时间通常被称为“周期时间”,但并不总是如此——在工业中,这通常与交货时间有着非常不同的含义。可变性和方差有时似乎也可以互换使用。这本书也非常关注按订单生产——不可否认,这是更困难的生产计划主题——但对按库存生产相关问题的讨论却相当少。这本书关注的是交货期,这对于库存生产来说是一个不太相关的KPI。其他一些高度相关的话题,如拉动式生产和看板,几乎没有被提及。一些章节包含了批判的观点,但是大多数章节留给读者去决定哪种方法是最适用的。另一方面,对这一领域的研究进行彻底的批判本身就是一项艰巨的任务。总的来说,这本书是一个结构化的指南,在生产计划领域的可用研究。这将有助于充实学术论文的文献综述部分。然而,它对真正挖掘论文并理解其背后的研究和数学的繁重工作的帮助要小得多。为了更深入的理解,原始资料将继续是必要的,但本书将有助于引导读者了解这些资料。
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Production planning with capacitated resources and congestion
The book gives a thorough and extensive overview of the research related to production planning. This is an important problem for industry, as the topic of production planning in practice still leaves much to be desired. Especially for job shops, production planning is seen as difficult, resulting in many inefficiencies and less-than-satisfying production performances. The first three chapters of the book serve as an overview and introduction, where the first chapter introduces the problem, the second chapter defines some relevant KPI, and the third chapter gives an overview of the different production planning frameworks. The book then starts to go deeper into the different frameworks for production planning. Chapter 4 focuses on the field of workload control, chapter 5 on models assuming fixed lead times, and chapter 6 on models for time-varying lead times. The subsequent chapters look deeper at clearing functions, with chapter 7 on univariate clearing functions, chapter 8 on multivariate clearing functions, chapter 9 on lot sizing in clearing functions, and chapter 10 on application of clearing functions before the final chapter 11 concludes the book. Overall, this book by the two authors who are well known in this field is a very thorough and extensive literature review of the existing research on production planning. It includes hundreds of references up to 2019. The aim of the book is to give a structured overview of existing research. In the authors own words, they want to ‘[... raise] more questions in the mind of the reader than [to answer ... ]’ (pg. 276). The target audience are academic researchers focussing on the field of production planning. The book is far up in the ivory tower, and has few uses for practitioners, either due to the limitations and assumptions of the models, or due to the mathematical complexity exceeding the ability of the average production professional. Even for academics it is a tough read, and most readers will likely focus on selected topics of the book rather than reading it cover to cover. Hence, it is not a large problem that the different sections are not well-integrated. For example, the mathematical nomenclature is not consistent even within chapters, and usually uses the variables as found in the source references. Some variables would also benefit from a more concise explanation or definition. Similar applies to the figures, which also frequently originate from the references and have vastly different styles. Other figures that seem original to the book lack rigour. The differentiation using colours will be lost in greyscale printing, lines are sometimes not straight, and text in figures is misaligned. In combination, this gives some illustrations and equations an unfinished appearance. It is a bit more problematic that the wording is also not consistent. For example, the lead time is often but not always called ‘cycle time’—which in industry often has a very different meaning than lead time. Variability and variance also seem to be sometimes used interchangeably. The book is also focussed very much on make-to-order production—admittedly the more difficult production planning topic—but is rather thin on make-to-stock related problems. The book focuses on lead time, which would be a less relevant KPI for make-to-stock production. Some other highly related topics like pull production and kanban get barely a passing mention. A few chapters include critical views, but most chapters leave it up to the reader to decide which method is most applicable. On the other hand, a thorough critique of the body of research in this field would be a monumental task on its own. Overall, this book is a structured guide to the available research in the field of production planning. It will help in fleshing out the literature review section for academic papers. However, it helps much less with the grunt work of actually digging through the papers and understanding the research and the mathematics behind them. For a deeper understanding, the original sources will continue to be necessary, but this book will helpfully guide the readers towards these sources.
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来源期刊
Production Planning & Control
Production Planning & Control 管理科学-工程:工业
CiteScore
19.30
自引率
9.60%
发文量
72
审稿时长
6-12 weeks
期刊介绍: Production Planning & Control is an international journal that focuses on research papers concerning operations management across industries. It emphasizes research originating from industrial needs that can provide guidance to managers and future researchers. Papers accepted by "Production Planning & Control" should address emerging industrial needs, clearly outlining the nature of the industrial problem. Any suitable research methods may be employed, and each paper should justify the method used. Case studies illustrating international significance are encouraged. Authors are encouraged to relate their work to existing knowledge in the field, particularly regarding its implications for management practice and future research agendas.
期刊最新文献
A framework for the systematic implementation of Green-Lean and sustainability in SMEs Exploring the barriers in medical additive manufacturing from an emerging economy Engaging with ‘Engineer for Supply Chain’ (EfSC): insights from two engineer-to-order manufacturers Towards a unified theory of supply chain value creation and capture Sustainable humanitarian supply chains: a systematic literature review and research propositions
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