Selecting advanced analytics in manufacturing: a decision support model
نویسندگان
چکیده
Advanced analytics offers new means by which to increase efficiency. However, real-world applications of advanced in manufacturing are scarce. One reason is that the management task selecting technologies (AATs) for application areas not well understood. In practice, choosing AATs difficult because a myriad potential techniques (e.g. diagnostic, predictive, and prescriptive) suitable different value chain planning, scheduling, or quality assurance). It thus challenging managers identify yield economic benefit. We propose multi-criteria decision model can use select efficient tailored company-specific needs. Based on data envelopment analysis, our evaluates efficiency each AAT with respect cost drivers performance across common manufacturing. The effectiveness demonstrated applying it two companies. For company, customized portfolio derived sample cases. Thereby, we aid decision-making concerning allocation corporate resources. Our only facilitates optimal financial operations short-term but also guides long-term strategic investments AATs.
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ژورنال
عنوان ژورنال: Production Planning & Control
سال: 2022
ISSN: ['0953-7287', '1366-5871']
DOI: https://doi.org/10.1080/09537287.2022.2126951