A maturity assessment model for manufacturing systems

Vivares, Jorge A.; Sarache, William; Hurtado, Jorge E.

doi:10.1108/jmtm-07-2017-0142

Cited by 30 publications

(13 citation statements)

References 52 publications

(60 reference statements)

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“…The descriptions are ordered into capability levels, from “not able to do it” to “continuously improving”. Most of the tools encompass five levels, although it is possible to find models with anywhere between three and nine levels (Vivares et al , 2018). Each level’s structure contains a set of goals that must be addressed to achieve maturity at that specific level, supporting sub-goals that define the scope, limits and necessary actions for a particular level, as well as activities and tasks that should be performed to achieve each level’s goals (Singh et al , 2015).…”

Section: Literature Reviewmentioning

confidence: 99%

Digital readiness assessment of Italian SMEs: a case-study research

Pirola

Cimini

Pinto

2019

JMTM

180

120

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Purpose Given the challenges that Industry 4.0 poses, the purpose of this paper is to propose a comprehensive assessment model suitable for evaluating small- and medium-size enterprises’ (SMEs) digital readiness levels, discuss the results of an assessment of 20 manufacturing SMEs using the proposed model and highlight priorities needed to undertake a successful journey towards Industry 4.0. Design/methodology/approach The research adopts an empirical approach using multiple case studies. Starting with a literature review about maturity and readiness-assessment models for Industry 4.0, the study’s model has been built and validated through two pilot case studies, with the final model used in an extensive case studies research with 20 enterprises. Findings The SMEs used in this research present an intermediate readiness level with respect to Industry 4.0. They are aware of the phenomenon, but management is still taking the first steps towards identifying the most appropriate strategy to approach this Fourth Industrial Revolution. Companies need to exploit all opportunities that data availability provides in terms of knowledge creation and decision-making support, in all forms, through investments in people skills and expertise and through an infrastructure that can support data gathering, analysis and sharing. Originality/value The Italian industrial landscape comprises mainly SMEs, mostly needing support to understand their path towards Industry 4.0. Therefore, the proposed model specifically focuses on SMEs, given its modularity, ease of understanding and fit to SMEs’ organisational structure. Furthermore, insights from 20 Italian SMEs are examined, and a list of priorities is highlighted.

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Section: Literature Reviewmentioning

confidence: 99%

Digital readiness assessment of Italian SMEs: a case-study research

Pirola

Cimini

Pinto

2019

JMTM

180

120

View full text Add to dashboard Cite

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“…To verify the suitability of each expert, the capability coefficient ( K ) was used (Equation (1)) (Evlanov and Kutuzov, 1978; Vivares et al , 2018). If K ⩾0.75, the expert may be selected.…”

Section: Methodology For Gscm Index Designmentioning

confidence: 99%

An integral GSCM index for assessment of environmental performance in manufacturing companies

Trujillo-Gallego

Sarache

2019

BIJ

Self Cite

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Purpose From the green supply chain management (GSCM) approach, the purpose of this paper is to propose a green index as a benchmarking tool to assess environmental performance in manufacturing companies. The index involves 10 green practices and 46 performance dimensions, which were identified by way of an exhaustive literature review. Design/methodology/approach The GSCM index was designed as follows: survey design; experts group selection; relationship identification and green practice weighting (DEMATEL method); and GSCM index construction. The proposed GSCM index was validated at a set of ten Colombian manufacturing companies, which belong to different industrial subsectors. Findings The structural relationships between both green practices and performance dimensions (cause group vs effect group) were determined. Consequently, a set of green practices and performance dimensions on which managers must focus their environmental efforts (cause group), in order to positively affect the system as a whole, was identified. The environmental performance of a set of manufacturing companies was established. Practical implications As a decision support tool, the GSCM index provides a baseline for the deployment of environmental improvement plans. It also permits the comparison of environmental performance between companies from different industrial sectors. Further, it can be used to monitor internal operations and collaboration programs in each echelon of the supply chain. Originality/value This publication contributes to the field of environmental performance measurement by introducing a new index, from the GSCM perspective. In contrast with the existing green indicators, the proposed index is the first to consider causal relationships between green practices and between their performance dimensions.

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“…Similar to change readiness, Industry 4.0 can be implemented in companies on three prime levels [23]. At "operations" level, reconfiguration of Industry 4.0 technologies is needed.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Embracing Industry 4.0: Empirical Insights from Malaysia

et al. 2021

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Industry 4.0 revolution, with its cutting-edge technologies, is an enabler for businesses, particularly in reducing the cost and improving the productivity. However, a large number of organizations are still too in their infancy to leverage the true potential of Industry 4.0 and its technologies. This paper takes a quantitative approach to reveal key insights from the companies that have implemented Industry 4.0 technologies. For this purpose, 238 technology companies in Malaysia were studied through a survey questionnaire. As technology companies are usually the first in line to adopt new technologies, they can be studied better as leaders in adopting the latest technologies. The findings of this descriptive study surfaced an array of insights in terms of Industry 4.0 readiness, Industry 4.0 technologies, leadership, strategy, and innovation. This research paper contributes by providing 10 key empirical insights on Industry 4.0 that can be utilized by managers to pace up their efforts towards digital transformation, and can help the policymakers in drafting the right policy to drive the digital revolution.

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A maturity assessment model for manufacturing systems

Cited by 30 publications

References 52 publications

Digital readiness assessment of Italian SMEs: a case-study research

Digital readiness assessment of Italian SMEs: a case-study research

An integral GSCM index for assessment of environmental performance in manufacturing companies

Embracing Industry 4.0: Empirical Insights from Malaysia

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