Smart retrofitting in manufacturing: A systematic review

Jaspert, David; Ebel, Martin; Eckhardt, Alexej; Pöppelbuß, Jens

doi:10.1016/j.jclepro.2021.127555

Cited by 51 publications

(37 citation statements)

References 61 publications

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“…In these cases, the same and other information useful for the purpose of this paper are extracted (gender, age estimation, eye-gaze tracking, and FR), although they are applied to User Experience (UX) analysis. Smart retrofitting, as defined by Jaspert et al [18] is described as "the integration of new technologies and sensors into legacy systems, supporting the transition towards real smart manufacturing. It can extend the life cycle of machinery and equipment in a way that is feasible, time-saving, and requires comparatively low investments".…”

Section: Related Workmentioning

confidence: 99%

Smart retrofitting for human factors: a face recognition-based system proposal

Generosi

Agostinelli

Mengoni

2022

Int J Interact Des Manuf

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Industry nowadays must deal with the so called “fourth industrial revolution”, i.e. Industry 4.0. This revolution is based on the introduction of new paradigms in the manufacturing industry such as flexibility, efficiency, safety, digitization, big data analysis and interconnection. However, human factors’ integration is usually not considered, although included as one of the paradigms. Some of these human factors’ most overlooked aspects are the customization of the worker’s user experience and on-board safety. Moreover, the issue of integrating state of the art technologies on legacy machines is also of utmost importance, as it can make a considerable difference on the economic and environmental aspects of their management, by extending the machine’s life cycle. In response to this issue, the Retrofitting paradigm, the addition of new technologies to legacy machines, has been considered. In this paper we propose a novel modular system architecture for secure authentication and worker’s log-in/log-out traceability based on face recognition and on state-of-the-art Deep Learning and Computer Vision techniques, as Convolutional Neural Networks. Starting from the proposed architecture, we developed and tested a device designed to retrofit legacy machines with such capabilities, keeping particular attention to the interface usability in the design phase, little considered in retrofitting applications along with other Human Factors, despite being one of the pillars of Industry 4.0. This research work’s results showed a dramatic improvement regarding machines on-board access safety.

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Section: Related Workmentioning

confidence: 99%

Smart retrofitting for human factors: a face recognition-based system proposal

Generosi

Agostinelli

Mengoni

2022

Int J Interact Des Manuf

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“…Blomeke et al [5] proposed a recycling 4.0 framework with integrated SM technologies and solutions to support recycling, reusing, and remanufacturing. Jaspert et al [48] referred to the reconfiguration of SM as smart retrofitting, and an SM could be retrofitted at any functional layer of an enterprise, from the physical, sensor, connectivity, and data layers, to the application layer. Most of the reported applications were in the preliminary stages and met the expectations only for certain aspects.…”

Section: Applicationsmentioning

confidence: 99%

Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective, Part I—Digital Triad Concept and Its Application as a System Reference Model

Zhang

et al. 2021

Machines

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Rapidly developed information technologies (IT) have continuously empowered manufacturing systems and accelerated the evolution of manufacturing system paradigms, and smart manufacturing (SM) has become one of the most promising paradigms. The study of SM has attracted a great deal of attention for researchers in academia and practitioners in industry. However, an obvious fact is that people with different backgrounds have different expectations for SM, and this has led to high diversity, ambiguity, and inconsistency in terms of definitions, reference models, performance matrices, and system design methodologies. It has been found that the state of the art SM research is limited in two aspects: (1) the highly diversified understandings of SM may lead to overlapped, missed, and non-systematic research efforts in advancing the theory and methodologies in the field of SM; (2) few works have been found that focus on the development of generic design methodologies for smart manufacturing systems from the practice perspective. The novelty of this paper consists of two main aspects which are reported in two parts respectively. In the first part, a simplified definition of SM is proposed to unify the existing diversified expectations, and a newly developed concept named digital triad (DT-II) is adopted to define a reference model for SM. The common features of smart manufacturing systems in various applications are identified as functional requirements (FRs) in systems design. To model a system that is capable of reconfiguring itself to adapt to changes, the concept of IoDTT is proposed as a reference model for smart manufacturing systems. In the second part, these two concepts are used to formulate a system design problem, and a generic methodology, based on axiomatic design theory (ADT), is proposed for the design of smart manufacturing systems.

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“…The latter process is known as smart retrofitting. Jaspert et al (2021) define Smart Retrofitting as the integration of new technologies into legacy systems to enable the transition towards Industry 4.0. It is an action that involves machinery that was not designed for the Industry 4.0 vision, and it aims to transfer the requirements of this vision to such machinery using the lowest time and capital investment (Guerreiro et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…The improvement of devices through smart retrofitting is a desirable outcome, as it enables Industry 4.0 transparency without the high investment and high risk associated with the replacement of machinery. Smart retrofitting has several advantages, such as ensuring competitiveness of enterprises, increasing equipment efficiency, and achieving sustainability (Jaspert et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…This work is interested in the study of smart retrofitting in the maintenance context: Smart Retrofitting in Maintenance (SRM). While Jaspert et al have already produced a literature review on smart retrofitting (Jaspert et al, 2021), they focus on the manufacturing domain. The main novelty of the present work is then to focus on the maintenance domain.…”

Section: Introductionmentioning

confidence: 99%

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Smart retrofitting in maintenance: a systematic literature review

2022

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The last decade saw the rise of digitalization and data-supported decision making in the manufacturing industry: the Fourth Industrial Revolution. This trend, also known as Industry 4.0, allows manufacturing enterprises to discover manufacturing uncertainties and measure their real manufacturing capability. One of the ways in which Industry 4.0 trends have been exploited is in the improvement of maintenance, which went from following planning-focused paradigms to more proactive-focused stances. Enabling the Industry 4.0 vision for maintenance purposes has historically required companies to either replace or upgrade their existing legacy devices. It is through the latter course of action that Smart retrofitting in maintenance (SRM) intends to bring value to enterprises. This work aims to present a systematic literature review on SRM, utilizing the oft-cited PRISMA methodology. Through this analysis, a definition of SRM that reflects the current state of the art is proposed. Furthermore, the research in SRM applied in the context of different maintenance strategies is assessed (i.e. reactive, planned, proactive and strategic maintenance), and the most common drivers and challenges in SRM are presented. Finally, a roadmap for the implementation of SRM is proposed. The analysis of the SRM literature reveals that there are important research opportunities in the exploitation of SRM for strategic maintenance and asset management. The authors hope that this document leads to the consolidation of a new research area that aims to add value to maintenance in enterprises through the application of smart retrofitting in preexisting legacy devices.

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Smart retrofitting in manufacturing: A systematic review

Cited by 51 publications

References 61 publications

Smart retrofitting for human factors: a face recognition-based system proposal

Smart retrofitting for human factors: a face recognition-based system proposal

Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective, Part I—Digital Triad Concept and Its Application as a System Reference Model

Smart retrofitting in maintenance: a systematic literature review

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