A support-design framework for Cooperative Robots systems in labor-intensive manufacturing processes

Ronzoni, Michele; Accorsi, Riccardo; Botti, Lucia; Manzini, Riccardo

doi:10.1016/j.jmsy.2021.10.008

Cited by 29 publications

(11 citation statements)

References 53 publications

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“…Weller et al, 2015;Rong et al, 2020) have argued that 3D printing allows higher product customization without incurring any cost penalties in manufacturing, facilitating the production of complex and integrated functional designs in a one-step process. In the same vein, collaborative robots are claimed to improve operational flexibility and efficiency towards higher customization (Li et al, 2021), even in labor-intensive manufacturing processes (Ronzoni et al, 2021). Our results add to these indications as we empirically evidenced that the implementation of both I4.0 technologies are especially encouraged in high-readiness companies whose manufacturing strategy is characterized by high product customization and low production volume.…”

Section: Resultssupporting

confidence: 69%

See 1 more Smart Citation

Industry 4.0: what is the relationship between manufacturing strategies, critical success factors and technology adoption?

Tortorella

Kurnia

Trentin

et al. 2022

JMTM

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PurposeThis paper examines the relationship between different manufacturing strategies and Industry 4.0's (I4.0) critical success factors (CSFs) and technology adoption.Design/methodology/approachFor that, the authors surveyed 165 practitioners from different manufacturers. Participants provided information about the levels of product customization and production volume in their companies. They also indicated the adoption level of I4.0 technologies and CSFs. Using multivariate data techniques, the authors identified four clusters of different manufacturing strategies and two readiness levels based on the establishment of I4.0 CSFs. The adoption level of I4.0 technologies was then cross compared among clusters to identify which technologies are more likely to be supported.FindingsThe findings indicate that, in low-readiness companies, the adoption level of I4.0 technologies does not significantly differ between manufacturing strategies. However, when companies present a higher I4.0 readiness, the adoption of I4.0 technologies seem to vary according to the existing manufacturing strategy.Originality/valueThis study sheds light on the influence that manufacturing strategies may have on the digital transformation of companies, highlighting which strategies are more likely to offer a context to successfully adopt I4.0 technologies. The identification of these relationships helps to define the expectation regarding the company's digital transformation, determining coherent benchmarks and allowing managers to anticipate potential issues.

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Section: Resultssupporting

confidence: 69%

“…In the same vein, collaborative robots are claimed to improve operational flexibility and efficiency towards higher customization (Li et al. , 2021), even in labor-intensive manufacturing processes (Ronzoni et al. , 2021).…”

Section: Resultsmentioning

confidence: 99%

Industry 4.0: what is the relationship between manufacturing strategies, critical success factors and technology adoption?

Tortorella

Kurnia

Trentin

et al. 2022

JMTM

View full text Add to dashboard Cite

show abstract

“…In recent times, industrial robots have transcended the concept of traditional mechanical equipment by integrating big data, artificial intelligence and cloud computing to become the core of the industrial interconnection system, thereby enabling IM. These robots are already being used in areas such as food processing, palletising and packaging and delivery, and by supporting the relevant design framework, collaborative robotic systems can aid factory layout, task scheduling design and economic and technical feasibility analysis (Ronzoni et al ., 2021). Furthermore, smart wireless sensors and actuator networks can be applied to support Internet of Things (IoT)‐based robotic intelligent systems for energy‐efficient management of devices, machines and processes (Blanco et al ., 2018).…”

Section: Resultsmentioning

confidence: 99%

A bibliometric review of progress and trends in food factory design research

Liu

Zhao

Liu

et al. 2022

Int J of Food Sci Tech

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Food factory design (FFD) affects production costs, production safety and food quality. Moreover, as consumer demand, product planning, policies and legislation, raw material supplies, manufacturing philosophies and environmental consciousness change, FFD should also change. In this study, we used bibliometric analysis to examine articles on a wide range of topics related to FFD published in Web of Science from 2012 to 2022. We used collaborative network analysis, co-occurrence analysis, cluster analysis, timeline mapping and term burst detection to achieve the following objectives: (i) summarising the annual changes in the number of publications; (ii) detecting influential countries and institutions, major research areas, context and history and representative studies at different times; and (iii) identifying frontiers and forecasting development trends in terms of factory construction and new production modes, new processes and product manufacturing technology, optimisation of production systems and processes, intelligent manufacturing, environmental protection and sustainable development. The findings of this study provide an effective means of assessing the performance of FFD research. They also help enterprises and researchers to identify important trends in FFD and provide support for decision-making and policy formulation, and future directions for research and teaching activities.

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“…However, collaboration interaction allows both operator and robot to always be in a direct connection and target the same task. The investment in developing collaborative working areas is increasing with specific interest given the ability of human operators to share and exchange information with robots to improve productivity and work efficiency [12]. This indicates the flexibility of creating a direct connection between the human operator and the robot [13].…”

Section: Definition and Classification For Human-robot Collaborationmentioning

confidence: 99%

An Overview of Human-Robot Collaboration in Smart Manufacturing

Othman

Yang

2022

2022 27th International Conference on Automation and Computing (ICAC)

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Industry 4.0, also termed smart manufacturing, has revolutionized the industrial world with cutting-edge technologies such as collaborative robots and artificial intelligence etc. Productivity and efficiency are two key factors that determine the success level of manufacturing. Therefore, many manufacturers have become so eager to adopt adaptive, intuitive, collaborative and smart techniques to improve the production lines, including key manufacturing machines and equipment. Therefore, robotic systems are playing an increasingly vital role in many industrial sectors, as they decrease the need for human labour and increase automation level. In addition, material waste can be also reduced since robots provide stability and accuracy during work. In turn, production times are reduced as well. Consequently, smart manufacturing areas need more advanced, flexible, and smart robotic systems to respond to market size changes and customization processes. As a result, currently, great research efforts are made to enrich the interactions between humans and robots in the work environment. This paper presents an overview of Human-Robot Collaboration (HRC) systems being employed in smart manufacturing to exploit the benefits of human experience and the capabilities of robotic systems. The research gaps, challenges and future work directions on HRC are highlighted and analyzed towards smart manufacturing.

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A support-design framework for Cooperative Robots systems in labor-intensive manufacturing processes

Cited by 29 publications

References 53 publications

Industry 4.0: what is the relationship between manufacturing strategies, critical success factors and technology adoption?

Industry 4.0: what is the relationship between manufacturing strategies, critical success factors and technology adoption?

A bibliometric review of progress and trends in food factory design research

An Overview of Human-Robot Collaboration in Smart Manufacturing

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