A Smart Algorithm for Personalizing the Workstation in the Assembly Process

Turk, Maja; Pipan, Miha; Šimić, Marko; Herakovič, Niko

doi:10.3390/app10238624

Cited by 7 publications

(4 citation statements)

References 30 publications

(44 reference statements)

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“…Figure 3 shows the block diagram of an MCA for step 2 of the assembly process for the actual worker who participated in the research. The values determined by the MCA for the individual configuration of the controlled components of the smart assembly workstation are calculated using empirically determined equations, described in [ 33 ]. The parameters read from the database are divided into three groups—worker, product, and complexity.…”

Section: Resultsmentioning

confidence: 99%

“…The MCA took into account the influential parameters of the worker, the type of assembly process, and the product [ 33 ]. The worker’s gender and anthropometric characteristics, described only as a function of body height, were considered.…”

Section: Methodsmentioning

confidence: 99%

“…Taking into account the assembly of the product at height, the worktable height is reduced during the assembly process according to the dimensions of the product along the Z -axis, resulting in a working height of »1.2« from Figure 1 . The determination of the influential parameters and their dependence on the configuration of the manual assembly workstation are described in more detail in the paper [ 33 ].…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Multi-Criterial Algorithm for the Efficient and Ergonomic Manual Assembly Process

Turk

Šimić

Pipan

et al. 2022

IJERPH

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Industry 4.0 introduces smart solutions throughout the company’s supply chain, including manual assembly, where the goal is to ensure shorter work cycle time, increase productivity and quality, while minimizing costs. Following the principles of this paradigm, this paper proposes a digital transformation of the manual assembly process by implementing a multi-criterial algorithm (MCA) for adjusting and configuring a human-centered smart manual assembly workstation to ensure efficient and ergonomic performance of the manual assembly process. The MCA takes into account various influential parameters, such as the anthropometry of the individual worker, gender, complexity of the assembly process, product characteristics, and product structure. The efficiency of the MCA was verified both in the laboratory environment with the time analysis and in the virtual environment using Digital Human Modelling through several ergonomic analyses. The results of the implementation of the MCA on a manual assembly workstation support the digital (re)design of the manual assembly process with the aim of creating an efficient and ergonomically suitable workstation for each worker, thus increasing the productivity and efficiency of the human-centered manual assembly process.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Multi-Criterial Algorithm for the Efficient and Ergonomic Manual Assembly Process

Turk

Šimić

Pipan

et al. 2022

IJERPH

Self Cite

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“…They pinpointed the current problems with smart healthcare and suggested solutions to solve them. Turk et al (2020) [6] presents a smart assembly system controlled by a smart algorithm through digital human modeling for the personalization of assembly workstations. Turk et al (2021) [7] studied the impact of SETs on the performance of a new manual assembly station.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Design of Smart Workplace through Multi-Objective Programming

2021

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Smart environments have proven very supportive to the improvement of the performance of people in different workplaces. Plenty of applications have been introduced spanning different settings including healthcare, ambient assisted living, homes, offices, and manufacturing environment, etc. However, subjectivity and ambiguity prevail in the majority of research, and still, up to date, rare approaches found quantitatively and objectively constructing or assessing the impact of smart enabling technologies on the performance of the subject environment. Further, no approaches have considered optimizing the adoption of those smart technologies with respect to objectives achievement. This article presents a novel optimization methodology for designing a smart workplace environment in conditions of ambiguity or fuzziness. The methodology begins with defining and weighing the overall goals and objectives of the workplace. The Prometthe multi-criterion decision-making technique is used to weigh the operational objectives with respect to the overall workplace goals. Next, the relation among basic building blocks of the model; namely: the operational objectives, smartness features, and smart enabling technologies are quantified, utilizing fuzzy relations. Then, the fuzzy goal programming techniques will be utilized to optimize the impact relation values while considering the budget constraint. The proposed optimization methodology is implemented on the development and optimization of the smart clinic, as a typical instance of the workplace.

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