Implementing industry 4.0 real-time performance management systems: the case of Schneider Electric

Robert, Marc; Giuliani, Philippe; Gurǎu, Cälin

doi:10.1080/09537287.2020.1810761

Cited by 55 publications

(46 citation statements)

References 83 publications

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“…interact [ 55 , 76 , 77 , 78 , 79 ] and the International Organization for Standardization ISO 22400 is a standard describing KPIs in manufacturing [ 19 , 28 , 29 , 80 ]. It focuses on performance measures that serve as the foundation for achieving continuous operational performance improvement in manufacturing through key performance indicators (KPIs) based on various measurements derived from the context of the operation [ 81 , 82 , 83 ]. Smart manufacturing standards are important to ISO, ANSI/ISA-95, and IEC [ 80 ].…”

Section: Methodologiesmentioning

confidence: 99%

Performance Measurement System and Quality Management in Data-Driven Industry 4.0: A Review

Tambare¹,

Meshram²,

Lee

et al. 2021

Sensors

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The birth of mass production started in the early 1900s. The manufacturing industries were transformed from mechanization to digitalization with the help of Information and Communication Technology (ICT). Now, the advancement of ICT and the Internet of Things has enabled smart manufacturing or Industry 4.0. Industry 4.0 refers to the various technologies that are transforming the way we work in manufacturing industries such as Internet of Things, cloud, big data, AI, robotics, blockchain, autonomous vehicles, enterprise software, etc. Additionally, the Industry 4.0 concept refers to new production patterns involving new technologies, manufacturing factors, and workforce organization. It changes the production process and creates a highly efficient production system that reduces production costs and improves product quality. The concept of Industry 4.0 is relatively new; there is high uncertainty, lack of knowledge and limited publication about the performance measurement and quality management with respect to Industry 4.0. Conversely, manufacturing companies are still struggling to understand the variety of Industry 4.0 technologies. Industrial standards are used to measure performance and manage the quality of the product and services. In order to fill this gap, our study focuses on how the manufacturing industries use different industrial standards to measure performance and manage the quality of the product and services. This paper reviews the current methods, industrial standards, key performance indicators (KPIs) used for performance measurement systems in data-driven Industry 4.0, and the case studies to understand how smart manufacturing companies are taking advantage of Industry 4.0. Furthermore, this article discusses the digitalization of quality called Quality 4.0, research challenges and opportunities in data-driven Industry 4.0 are discussed.

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Section: Methodologiesmentioning

confidence: 99%

Performance Measurement System and Quality Management in Data-Driven Industry 4.0: A Review

Tambare¹,

Meshram²,

Lee

et al. 2021

Sensors

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“…Robert et al [46] Performance management model was developed by Schneider Electric to transform conventional manufacturing system into smart industry. Human factors and ergonomics were identified as core components along with technological system.…”

Section: Case Studymentioning

confidence: 99%

Analyzing Roadblocks of Industry 4.0 Adoption Using Graph Theory and Matrix Approach

Virmani

Salve

Luthra³

2023

IEEE Trans. Eng. Manage.

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The manufacturing era is going through an evolutionary phase from Industry 3.0 to Industry 4.0 (I4.0). In 2011, Germany initiated I4.0 during the Hanover fair in collaboration with industrialists, academicians and researchers. The benefits of implementing I4.0 are attracting the curiosity of practitioners. In current academic literature, there is little discussion related to analysing potential roadblocks of I4.0 implementation using mathematical modelling. This paper has identified roadblocks through an extensive literature review and validation has been carried out by gathering experts' opinions. As per the findings, the identified roadblocks have been categorized into five sections: management roadblocks, operational roadblocks, human resource roadblocks, procedural and behavioural roadblocks.A case study of the automobile industry has been discussed. The data was collected from experts in the area of I4.0. A Graph Theory and Matrix Approach (GTMA) was applied to evaluate the relative intensity of the roadblocks, Comprehensive I4.0 Index (CII) and its range for each category of roadblock. Implications for industrialists, practitioners and academicians are provided.

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“…This scenario opens new issues on the technologies adopted (He et al, 2021 ) and on the marketing processes (Kang et al, 2020 ) supported by such digitalization during the pandemic, specifically as far as customer relationship management is concerned. Research on digital transformation highlights that technologies have different characteristics in terms of potentiality for marketing purposes and in terms of time required for implementation (Robert et al, 2020 ). Previous studies show that both the adoption rate and the implementation process of the different digital technologies (the more mature web-based technologies and the more recent Industry 4.0 technologies) is uneven among firms of different sizes and industries (Bettiol et al, 2020a ).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Reacting to the COVID-19 pandemic through digital connectivity with customers: the Italian experience

et al. 2021

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The COVID-19 has deeply impacted the firm’s competitiveness because of the restrictions that limited the relationships with existing and new customers. The pandemic has pushed firms to rely on digital technologies to redefine business processes as well as customer relationships and marketing strategies. The digital technological portfolio firms may rely on to face the COVID-19 related challenges spanning from the established web-based technologies to the more recent Industry 4.0 tools related to the fourth industrial revolution. In this regard, the paper aims at exploring which digital technologies allowed firms to positively react to the pandemic to overcome their constraints in managing the market relationships. Based on an original qualitative analysis on 26 Italian SMEs carried out during the first Italian lockdown in 2020, the paper identifies three strategies in the use of digital technologies to support customer relationship management and market expansion. It emerges specifically the strategic importance of web-based technologies (videoconferencing, CRM and e-commerce) to support firm competition and performance through customer interactions and digital experience, advancing the literature on firms’ reaction strategies during turbulent and crisis times.

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Implementing industry 4.0 real-time performance management systems: the case of Schneider Electric

Cited by 55 publications

References 83 publications

Performance Measurement System and Quality Management in Data-Driven Industry 4.0: A Review

Performance Measurement System and Quality Management in Data-Driven Industry 4.0: A Review

Analyzing Roadblocks of Industry 4.0 Adoption Using Graph Theory and Matrix Approach

Reacting to the COVID-19 pandemic through digital connectivity with customers: the Italian experience

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