Flexibility based Assessment of Production System Robustness

Luft, Nils; Besenfelder, Christoph

doi:10.1016/j.procir.2014.06.141

Cited by 6 publications

(3 citation statements)

References 32 publications

(37 reference statements)

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“…It is important to understand their correspondences. For example, Lufi and Besenfelder [81] investigated the dependence of robustness on system flexibility of manufacturing systems since system flexibility tackled with volatile and unpredictable environments and a manufacturing system should make a trade-off between optimization and robustness for the best interest of system performance. Mass personalization needs high-level flexibility and responsiveness of a manufacturing system to make personalized products in small batch sizes cost-effectively.…”

Section: Flexibilitymentioning

confidence: 99%

Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective. Part II—Systematic Designs of Smart Manufacturing Systems

Zhang

et al. 2021

Machines

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In a traditional system paradigm, an enterprise reference model provides the guide for practitioners to select manufacturing elements, configure elements into a manufacturing system, and model system options for evaluation and comparison of system solutions against given performance metrics. However, a smart manufacturing system aims to reconfigure different systems in achieving high-level smartness in its system lifecycle; moreover, each smart system is customized in terms of the constraints of manufacturing resources and the prioritized performance metrics to achieve system smartness. Few works were found on the development of systematic methodologies for the design of smart manufacturing systems. The novel contributions of the presented work are at two aspects: (1) unified definitions of digital functional elements and manufacturing systems have been proposed; they are generalized to have all digitized characteristics and they are customizable to any manufacturing system with specified manufacturing resources and goals of smartness and (2) a systematic design methodology has been proposed; it can serve as the guide for designs of smart manufacturing systems in specified applications. The presented work consists of two separated parts. In the first part of paper, a simplified definition of smart manufacturing (SM) is proposed to unify the diversified expectations and a newly developed concept digital triad (DT-II) is adopted to define a generic reference model to represent essential features of smart manufacturing systems. In the second part of the paper, the axiomatic design theory (ADT) is adopted and expanded as the generic design methodology for design, analysis, and assessment of smart manufacturing systems. Three case studies are reviewed to illustrate the applications of the proposed methodology, and the future research directions towards smart manufacturing are discussed as a summary in the second part.

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Section: Flexibilitymentioning

confidence: 99%

Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective. Part II—Systematic Designs of Smart Manufacturing Systems

Zhang

et al. 2021

Machines

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show abstract

“…The stability, regarding a certain production system, is mostly related to preselected KPIs. For a robust production system the chosen KPIs would not deviate much under varying conditions" Luft and Besenfelder (2014) Production planning "[Robustness is] a property of a system which allows it to satisfy a fixed set of requirements, despite changes occurring after the system has entered service, in the environment or within the system itself, from the nominal or expected environment or the system design parameters" (based on Saleh et al, 2001) Mondal et al (2014 Manufacturing process modelling and evaluation "A robust manufacturing process is defined to be a process which maintains its acceptable performance consistently in a desired level even if there may be significant and substantial changes occurring in the levels of input variables and noise parameters during a given period of time or planning horizon" Stricker and Lanza (2014b) Production system faced with disturbances ". .…”

Section: Proposed Definition Of Robustness In Production Systemsmentioning

confidence: 99%

“…Besides defining what robustness represents in production systems, a comprehensive concept should also touch relations to adjacent terms. We consider flexibility, agility, resilience and resistance as the most important capabilities adjacent to robustness in the context of production, due to the fact that these terms are all mentioned to some extent in the relevant sample of the literature overview (Stricker et al, 2015;Luft and Besenfelder, 2014;Stricker and Lanza, 2014b). Flexibility can be described as the ability of a system to change and react efficiently to changing circumstances (Mishra, 2016;Upton, 1994;Gerwin, 1993).…”

Section: Relations Between Robustness and Adjacent System Capabilitiesmentioning

confidence: 99%

Robustness assessment in production systems

Stockmann

Winkler

Kunath

2021

JMTM

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PurposeThe concept of robustness in manufacturing is not easy to capture and even harder to quantify. This paper elaborates an approach to assess robustness in production systems from a holistic input-throughput-output perspective using a pragmatic robustness indicator.Design/methodology/approachFirst, in order to have a precise understanding of what needs to be measured, a concept of robustness in production systems is defined based on a literature overview. Three different aspects are considered to be essential to comprehensively describe robustness in production: the deviations of input resources, of performance and of output. These aspects are translated into an aggregated indicator based on developments of production costs, order delays and output volumes. The indicator-based assessment approach is eventually applied to a flow-shop scheduling case study in the chipboard industry.FindingsThe study shows that an assessment of robustness should not solely focus on a single aspect of a production system. Instead, a holistic view is required addressing the tradeoffs that robustness must balance, such as the one between the realized performance, the corresponding resource requirements and the resulting output. Furthermore, the study emphasizes that robustness can be interpreted as a superior system capability that builds upon flexibility, agility, resilience and resistance.Research limitations/implicationsFirst, the paper is a call to further test and validate the proposed approach in industry case studies. Second, the paper suggests a modified understanding of robustness in production systems in which not only the deviation of one single variable is of interest but also the behavior of the whole system.Practical implicationsThe approach allows practitioners to pragmatically evaluate a production system’s robustness level while quickly identifying drivers, barriers and tradeoffs.Originality/valueCompared to existing assessment approaches the proposed methodology is one of the first that evaluates robustness in production systems from a holistic input-throughput-output perspective highlighting the different tradeoffs that have to be balanced. It is based upon a comprehensive concept of robustness which also links robustness to adjacent capabilities that were otherwise only treated separately.

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Robustness of production systems: Evidence from the German manufacturing industry

Stockmann

Winkler

2022

Journal of Engineering and Technology Management

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Flexibility based Assessment of Production System Robustness

Cited by 6 publications

References 32 publications

Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective. Part II—Systematic Designs of Smart Manufacturing Systems

Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective. Part II—Systematic Designs of Smart Manufacturing Systems

Robustness assessment in production systems

Robustness of production systems: Evidence from the German manufacturing industry

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