产品复杂性对装配和拆卸操作中人类学习的影响

IF 7.3 2区 工程技术 Q1 ENGINEERING, INDUSTRIAL
E. Verna, G. Genta, M. Galetto
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引用次数: 0

摘要

目的本文的目的是研究和量化产品复杂性(包括体系结构复杂性)对装配和拆卸操作中操作员学习、生产力和质量性能的影响。这一主题在以前的研究中没有得到广泛的研究。设计/方法/方法进行了一项涉及84名操作员的广泛实验活动,反复组装和拆卸六种不同复杂度的产品,以构建生产力和质量学习曲线。使用统计学方法对实验数据进行分析。发现生产力的人类学习因素随着产品体系结构复杂性的增加而超线性增加,即从集中式到分布式体系结构,无论组装和拆卸,无论产品的整体复杂性如何。另一方面,随着产品体系结构复杂性的增加,质量性能的人类学习因素急剧下降。产品架构的内在特征是造成这种学习因素差异的原因。实际意义研究结果表明,在制造过程的设计和规划中考虑产品复杂性,特别是架构复杂性,可以优化操作员的学习、生产力和质量表现,并为改进制造运营的决策提供信息。独创性/价值虽然之前的研究侧重于复杂性对工艺时间和缺陷产生的影响,但本研究是第一批通过广泛的实验活动调查和量化产品复杂性(包括架构复杂性)对操作员学习的影响的研究之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of product complexity on human learning in assembly and disassembly operations
PurposeThe purpose of this paper is to investigate and quantify the impact of product complexity, including architectural complexity, on operator learning, productivity and quality performance in both assembly and disassembly operations. This topic has not been extensively investigated in previous research.Design/methodology/approachAn extensive experimental campaign involving 84 operators was conducted to repeatedly assemble and disassemble six different products of varying complexity to construct productivity and quality learning curves. Data from the experiment were analysed using statistical methods.FindingsThe human learning factor of productivity increases superlinearly with the increasing architectural complexity of products, i.e. from centralised to distributed architectures, both in assembly and disassembly, regardless of the level of overall product complexity. On the other hand, the human learning factor of quality performance decreases superlinearly as the architectural complexity of products increases. The intrinsic characteristics of product architecture are the reasons for this difference in learning factor.Practical implicationsThe results of the study suggest that considering product complexity, particularly architectural complexity, in the design and planning of manufacturing processes can optimise operator learning, productivity and quality performance, and inform decisions about improving manufacturing operations.Originality/valueWhile previous research has focussed on the effects of complexity on process time and defect generation, this study is amongst the first to investigate and quantify the effects of product complexity, including architectural complexity, on operator learning using an extensive experimental campaign.
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来源期刊
Journal of Manufacturing Technology Management
Journal of Manufacturing Technology Management Engineering-Control and Systems Engineering
CiteScore
16.30
自引率
7.90%
发文量
45
期刊介绍: The Journal of Manufacturing Technology Management (JMTM) aspires to be the premier destination for impactful manufacturing-related research. JMTM provides comprehensive international coverage of topics pertaining to the management of manufacturing technology, focusing on bridging theoretical advancements with practical applications to enhance manufacturing practices. JMTM seeks articles grounded in empirical evidence, such as surveys, case studies, and action research, to ensure relevance and applicability. All submissions should include a thorough literature review to contextualize the study within the field and clearly demonstrate how the research contributes significantly and originally by comparing and contrasting its findings with existing knowledge. Articles should directly address management of manufacturing technology and offer insights with broad applicability.
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