Implementing Machine Learning in Small and Medium-Sized Manufacturing Enterprises

Iftikhar, Nadeem; Nordbjerg, Finn Ebertsen

doi:10.1007/978-3-030-90700-6_51

Cited by 6 publications

(12 citation statements)

References 11 publications

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“…Technical [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], 17…”

Section: Inclusion-exclusion Criteriamentioning

confidence: 99%

“…[51]- [53], [39], [54], [58] 23 RQ3 RQ3.2 Tools [25], [26], [28], [30], [48], [31], [38], [55]- [57] 10…”

Section: Inclusion-exclusion Criteriaunclassified

“…, [26], [27], [40], [43], [41], [33], [28], [34], [44], [29], [35], [45], [46], [48], [50], [51], [52], [36], [53], [54], [57], [58], 23…”

Section: Inclusion-exclusion Criteriaunclassified

“…These technologies need a systematic and pragmatic methods to incorporate it in SME use cased of predictive maintenance [27]. One of the main characteristics of predictive modeling is that it does not depend on the standard programming practices like object-oriented design principles, but the algorithms learn from data [54] during the training phase. The second feature of predictive maintenance is that once the models are trained then it dependency on history data is limited and system is matured day by day in continuous online learning paradigm.…”

Section: Distinctive Characteristics (Rq3)mentioning

confidence: 99%

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A Systematic Mapping Study of Predictive Maintenance in SMEs

et al. 2022

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The rapid growth of Industry 4.0 and predictive methods fostered a great potential for state-of-the-art techniques in the industrial sector, especially in smart factories. The equipment failure or system breakdowns during run time of a factory creates a severe problems towards impoverishment of the production system and destitution of the business. Predictive Maintenance (PdM) is a cost-saving and data driven technique to predict the maintenance time of in-service equipment or systems to reduce breakdown time and increase productivity. Although PdM is pragmatically adopted in large-scale industries, there is a lack of studies that map the PdM adoption in small and medium-sized enterprises (SMEs). In this systematic mapping study (SMS), we focus on predictive maintenance from an SME perspective to explore the field for researchers, scientists, and developers to comprehend the potential of PdM systems, their challenges, distinctive characteristics, and best practices in SMEs. Our study is based on four research questions comprised of demographic data, key challenges, distinctive characteristics, and best practices of predictive maintenance in SMEs. We found that the current literature on PdM is deficient in the SME domain, especially the financial side is vague. There is a huge potential for PdM in SMEs to design cost models and focus on data availability impediments. Management and monitoring of PdM and skilled personnel are also inadequate. Thus, we present a study that extracts the knowledge from the existing literature about PdM in SMEs, finds the research gap, and can assist in identifying the barriers and challenges of PdM adoption in SMEs.

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“…Technical [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], 17…”

Section: Inclusion-exclusion Criteriamentioning

confidence: 99%

“…[51]- [53], [39], [54], [58] 23 RQ3 RQ3.2 Tools [25], [26], [28], [30], [48], [31], [38], [55]- [57] 10…”

Section: Inclusion-exclusion Criteriaunclassified

“…, [26], [27], [40], [43], [41], [33], [28], [34], [44], [29], [35], [45], [46], [48], [50], [51], [52], [36], [53], [54], [57], [58], 23…”

Section: Inclusion-exclusion Criteriaunclassified

Section: Distinctive Characteristics (Rq3)mentioning

confidence: 99%

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A Systematic Mapping Study of Predictive Maintenance in SMEs

et al. 2022

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“…A study of using AI in an SME suggested using open alliances with non-competing SMEs to set up a test-driven environment to enhance the knowledge of AI. The study also suggested to start using solvable problems and low-cost areas [144].…”

Section: Use Cases Of Aimentioning

confidence: 99%

AI and IoT for Production Data Analytics in SMEs

Hansen¹

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Artificial Intelligence and Machine Learning

Hansen

Bøgh²

2022

The Future of Smart Production for SMEs

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Implementing Machine Learning in Small and Medium-Sized Manufacturing Enterprises

Cited by 6 publications

References 11 publications

A Systematic Mapping Study of Predictive Maintenance in SMEs

A Systematic Mapping Study of Predictive Maintenance in SMEs

AI and IoT for Production Data Analytics in SMEs

Artificial Intelligence and Machine Learning

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