Manufacturing Strategy

Cohen, Morris A.; Lee, Hau L.

doi:10.1007/978-1-4613-2507-9_6

Cited by 27 publications

(3 citation statements)

References 7 publications

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“…The development of strategies that seek to improve the performance of manufacturing operations is a critical component of the competitive strategy of companies (Cohen and Lee, 1985;. A manufacturing strategy consists of a set of well-coordinated objectives and decisions to assure long-term, sustainable advantages that are aligned with the company's vision (Ward and Duray, 2000;Hill, 2017).…”

Section: Manufacturing Strategymentioning

confidence: 99%

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Industry 4.0: what is the relationship between manufacturing strategies, critical success factors and technology adoption?

Tortorella

Kurnia

Trentin

et al. 2022

JMTM

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PurposeThis paper examines the relationship between different manufacturing strategies and Industry 4.0's (I4.0) critical success factors (CSFs) and technology adoption.Design/methodology/approachFor that, the authors surveyed 165 practitioners from different manufacturers. Participants provided information about the levels of product customization and production volume in their companies. They also indicated the adoption level of I4.0 technologies and CSFs. Using multivariate data techniques, the authors identified four clusters of different manufacturing strategies and two readiness levels based on the establishment of I4.0 CSFs. The adoption level of I4.0 technologies was then cross compared among clusters to identify which technologies are more likely to be supported.FindingsThe findings indicate that, in low-readiness companies, the adoption level of I4.0 technologies does not significantly differ between manufacturing strategies. However, when companies present a higher I4.0 readiness, the adoption of I4.0 technologies seem to vary according to the existing manufacturing strategy.Originality/valueThis study sheds light on the influence that manufacturing strategies may have on the digital transformation of companies, highlighting which strategies are more likely to offer a context to successfully adopt I4.0 technologies. The identification of these relationships helps to define the expectation regarding the company's digital transformation, determining coherent benchmarks and allowing managers to anticipate potential issues.

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Section: Manufacturing Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Industry 4.0: what is the relationship between manufacturing strategies, critical success factors and technology adoption?

Tortorella

Kurnia

Trentin

et al. 2022

JMTM

View full text Add to dashboard Cite

show abstract

“…Since then, mathematical programming, heuristics, simulation and artificial intelligence have largely been used to design a distribution chain (or production‐distribution network as called in those papers). Cohen and Lee (1985), and Dogan and Goetschalckx (1999) considered multi‐commodity single‐product production‐distribution systems, and used mathematical programming methods to determine the locations of facilities by minimizing cost or maximizing profit. To make the design more valuable in practice, Jayaraman (1998) extended the model into a multi‐product situation, and different production methods were considered in his design model.…”

Section: Mathematics For Distribution Chain Designmentioning

confidence: 99%

An iterative approach for distribution chain design in agile virtual environment

Davidrajuh

2005

Industrial Management &Amp; Data Systems

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Purpose -The study sets out to explore the use of an iterative approach for designing distribution chain in an agile virtual environment; in an agile virtual environment, quick adaptation to changing market situation and automation of supply chain management processes are essential. Design/methodology/approach -The iterative approach consists of two parts: the strategic model and the tactical model. First, the strategic model (including number of distributors, location of distributors) is determined. Then, based on the output of the strategic model, the tactical model (i.e. the inventory planning at each node, and vehicle routeing between different nodes of the chain) is determined. After determining the tactical model, the operation-related parameters from the tactical model are input into the strategic model again, and the configuration of distribution chain is re-optimized. Such iterations proceed until the design result converges. Findings -The proposed iterative design process provides many advantages such as reuse of knowledge, adaptive to changing market conditions, modular design, and optimal results guaranteed by mixed mathematical usage. The proposed approach is also realizable as a supply chain management software tool. Originality/value -An important contribution of this study is the iterative process that uses three different types of mathematics. For determination of the strategic model mixed integer programming is used. Determination of the tactical model is effected using genetic algorithm and probability theory.

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Bridging the Gap Between Production, Finances, and Risk in Supply Chain Optimization

Puigjaner

Guillén‐Gosálbez

2010

Process Systems Engineering

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Manufacturing Strategy

Cited by 27 publications

References 7 publications

Industry 4.0: what is the relationship between manufacturing strategies, critical success factors and technology adoption?

Industry 4.0: what is the relationship between manufacturing strategies, critical success factors and technology adoption?

An iterative approach for distribution chain design in agile virtual environment

Bridging the Gap Between Production, Finances, and Risk in Supply Chain Optimization

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