From legacy-based factories to smart factories level 2 according to the industry 4.0

Orellana, Felipe; Torres, Romina

doi:10.1080/0951192x.2019.1609702

Cited by 34 publications

(42 citation statements)

References 16 publications

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“…Literature (Orellana and Torres 2019;Helo and Shamsuzzoha 2020;Huang et al 2019;Lee et al 2018;Hwang et al 2017) shows that the availability of indicators to assess the impact of the operation on the set objectives at real-time is used to facilitate continuous improvement processes. Fawcett and Cooper (1998) conducted a survey study with 111 firms, in which the higher-performing firms were found to place greater emphasis on performance measurement.…”

Section: Discussion and Further Research Directionsmentioning

confidence: 99%

Automated Performance Measurement in Internal Logistics Systems

Raith

Woschank

Zsifkovits

2021

Implementing Industry 4.0 in SMEs

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In addition to economic and on-time order fulfillment, the monitoring of the plant performance and its related key performance indicators is a central task of logistics management and control systems. Currently, the determination and calculation of performance figures within the framework of site acceptance tests of automated logistics systems are plant-specific and, therefore, require a lot of manual effort. In this chapter, the authors develop a concept for the automated determination of performance indicators for storage and conveying systems. Based on a comprehensive literature review, structured expert interviews and including various perspectives from industrial applications the approach is designed. Further, the impact of the proposed concept on the logistics performance of the plant and the adequate selection of a maintenance strategy is discussed.

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Section: Discussion and Further Research Directionsmentioning

confidence: 99%

Automated Performance Measurement in Internal Logistics Systems

Raith

Woschank

Zsifkovits

2021

Implementing Industry 4.0 in SMEs

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“…Therefore, correctly identifying the smart factory stakeholders and understanding their requirements is crucial [110]. Transforming a traditional factory-using legacy machines-into a smart factory is possible without buying expensive new machines, employing a continuous improvement approach, the IoT as enabling technology and establishing visible KPIs from the beginning so that the path to Industry 4.0 is clear to all stakeholders [111]. The increased network complexity and data traffic increase the probabilities of IoT failure.…”

Section: Key Performance Indicators For Industry 40mentioning

confidence: 99%

Lean Manual Assembly 4.0: A Systematic Review

2020

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In a demand context of mass customization, shifting towards the mass personalization of products, assembly operations face the trade-off between highly productive automated systems and flexible manual operators. Novel digital technologies—conceptualized as Industry 4.0—suggest the possibility of simultaneously achieving superior productivity and flexibility. This article aims to address how Industry 4.0 technologies could improve the productivity, flexibility and quality of assembly operations. A systematic literature review was carried out, including 234 peer-reviewed articles from 2010–2020. As a result, the analysis was structured addressing four sets of research questions regarding (1) assembly for mass customization; (2) Industry 4.0 and performance evaluation; (3) Lean production as a starting point for smart factories, and (4) the implications of Industry 4.0 for people in assembly operations. It was found that mass customization brings great complexity that needs to be addressed at different levels from a holistic point of view; that Industry 4.0 offers powerful tools to achieve superior productivity and flexibility in assembly; that Lean is a great starting point for implementing such changes; and that people need to be considered central to Assembly 4.0. Developing methodologies for implementing Industry 4.0 to achieve specific business goals remains an open research topic.

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“…Despite this, it is evident that there are certain clusters of technologies that have formed and now drive ongoing digital transformation endeavors, which may also offer the most appropriate base for Industry 4.0 consideration in our study [ 1 , 53 ]: Internet of Things (IoT), which integrates various processes with information and communication technologies, cloud computing, smart objects, and machines, leading to cyber–physical systems [ 54 , 55 , 56 ]; Cyber–Physical Systems (CPS), which use advanced technologies, big data, and real-time two-way communications to control production (and broader business) processes and systems [ 57 , 58 ]; Smart Factories, which are smaller and decentralized production units that are digitalized and autonomous [ 26 ]. This stage of integration is resulting in processes being much more efficient and productive [ 59 ]. …”

Section: Theoretical Background and Hypotheses Developmentmentioning

confidence: 99%

“…Smart Factories, which are smaller and decentralized production units that are digitalized and autonomous [ 26 ]. This stage of integration is resulting in processes being much more efficient and productive [ 59 ].…”

Section: Theoretical Background and Hypotheses Developmentmentioning

confidence: 99%

Speeding Up the Implementation of Industry 4.0 with Management Tools: Empirical Investigations in Manufacturing Organizations

Črešnar

Potočan

Nedelko

2020

Sensors

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The main purpose of this study is to examine how the use of management tools supports the readiness of manufacturing organizations for the implementation of Industry 4.0. The originality of the research is reflected in the exploration of the relationship between the use of the selected well-known management tools and their readiness for the implementation of Industry 4.0, which was assessed using a combination of two models—one developed by the National Academy of Science and Engineering (Acatech) and the other by the University of Warwick. The relationship was assessed by applying structural equation modeling techniques to a data set of 323 responses from employees in manufacturing organizations. The results show that the use of six sigma, total quality management, radio frequency identification, a balanced scorecard, rapid prototyping, customer segmentation, mission and vision statements, and digital transformation is positively associated with Industry 4.0 readiness. Inversely, outsourcing and strategic planning are negatively associated with Industry 4.0 readiness, while lean manufacturing, which is often emphasized as the cornerstone of Industry 4.0 implementation, is not associated with Industry 4.0 readiness in our study. These findings can help organizations to understand how to consider and measure readiness for the implementation of Industry 4.0 more comprehensively and present guidelines on how the use of management tools in manufacturing organizations can foster their implementation of Industry 4.0 principles.

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From legacy-based factories to smart factories level 2 according to the industry 4.0

Cited by 34 publications

References 16 publications

Automated Performance Measurement in Internal Logistics Systems

Automated Performance Measurement in Internal Logistics Systems

Lean Manual Assembly 4.0: A Systematic Review

Speeding Up the Implementation of Industry 4.0 with Management Tools: Empirical Investigations in Manufacturing Organizations

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