A two-level optimisation-simulation method for production planning and scheduling: the industrial case of a human–robot collaborative assembly line

Vieira, Miguel; Moniz, Samuel; Gonçalves, Bruno S.; Pinto‐Varela, Tânia; Barbosa‐Póvoa, Ana Paula; Neto, Pedro

doi:10.1080/00207543.2021.1906461

Cited by 20 publications

(4 citation statements)

References 48 publications

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“…Gualtieri et al, (2020a) provided a guideline for designing a product that improves the productivity of the collaborative assembly lines. Xu et al (2021), Li et al, (2021c), Vieira et al (2022), Li et al (2022), and Keshvarparast et al (2022) developed a multi-objective mathematical model in which one of the objective functions was to improve productivity. Zhang et al, (2021b) applied a new metric, a combination of productivity and ergonomics, to design a collaborative assembly line.…”

Section: Productivitymentioning

confidence: 99%

“…Li et al, (2021c) proposed a bi-objective mathematical model with the second objective function being the minimization of the cost of the assembly line. Fager et al (2021) calculated the cost-effectiveness of using Cobots in a picking system Vieira et al (2022). developed a two-level mathematical model with a detailed discrete-event simulation model Peron et al (2022).…”

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confidence: 99%

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Collaborative robots in manufacturing and assembly systems: literature review and future research agenda

et al. 2023

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Nowadays, considering the constant changes in customers’ demands, manufacturing systems tend to move more and more towards customization while ensuring the expected reactivity. In addition, more attention is given to the human factors to, on the one hand, create opportunities for improving the work conditions such as safety and, on the other hand, reduce the risks brought by new technologies such as job cannibalization. Meanwhile, Industry 4.0 offers new ways to facilitate this change by enhancing human–machine interactions using Collaborative Robots (Cobots). Recent research studies have shown that cobots may bring numerous advantages to manufacturing systems, especially by improving their flexibility. This research investigates the impacts of the integration of cobots in the context of assembly and disassembly lines. For this purpose, a Systematic Literature Review (SLR) is performed. The existing contributions are classified on the basis of the subject of study, methodology, methodology, performance criteria, and type of Human-Cobot collaboration. Managerial insights are provided, and research perspectives are discussed.

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Section: Productivitymentioning

confidence: 99%

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confidence: 99%

Collaborative robots in manufacturing and assembly systems: literature review and future research agenda

et al. 2023

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“…For instance, Jung et al (2004) solves a deterministic lot-sizing problem and iteratively adjusts the safety stock after evaluation in simulation that accounts for uncertain demand. This iterative approach was also recently applied for planning in a collaborative assembly line (Vieira et al 2021), and for planning in a wafer fabrication production plant (Kim and Lee 2016).…”

Section: Simulation-optimization Approachesmentioning

confidence: 99%

A state-of-the-art on production planning in Industry 4.0

Luo

Thevenin

Dolgui

2022

International Journal of Production Research

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The Industry 4.0 revolution is changing the manufacturing landscape. A broad set of new technologies emerged (including software and connected equipment) that digitize manufacturing systems. These technologies bring new vitality and opportunities to the manufacturing industry, but they also bring new challenges. This paper focuses on the impact of Industry 4.0 on production planning approaches and software. We first propose a digital twin framework that integrates production planning systems and frontier technologies. The frontier technologies that may impact production planning software are the internet of things, cloud manufacturing, blockchain, and big data analytics. Second, we provide a state-of-the-art on the application of each technology in the production planning, as well as a detailed analysis of the benefit and application status. Finally, this paper discusses the future research and application directions in the production planning. We conclude that Industry 4.0 will lead to the construction of data-driven models for production planning software. These tools will include models built accurately from data, account for uncertainty, and partially actuate the decision autonomously.

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“…Demand uncertainty can affect consumer expectations of product purchases and production processes (Dev et al, 2020). Forecasting demand for consumer needs, the amount of Stock available in the company, and production costs for the number of products produced are critical factors in production planning decisions (Vieira et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Smart Production Planning Model for T-Shirt Products at Raensa Convection

Santosa¹,

Hidayat²,

Siskandar³

et al. 2023

JITI

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The increasing stock condition of cotton combed 30s t-shirts causes Convection to require optimal production planning, influenced by demand, safety stock, and selling price. The analysis of forecasting demand for t-shirts obtained a need for 217 t-shirts using the Multiplicative Decomposition forecasting method with MAD = 22.47 and MAPE = 0.17. Based on demand data for 1 year, the Safety Stock that must be maintained is 126 shirts/month or 3 shirts/week. The optimal production defuzzification results are 369 t-shirts with 81 fuzzy rules used. The Master Production Planning (MPS) directs the production schedule to be carried out in January, scheduled for the 4th week of December the previous year, as many as 123 shirts and ended on the third Sunday in January as many as 92 shirts to maintain stock conditions and meet the demand of consumer.

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A two-level optimisation-simulation method for production planning and scheduling: the industrial case of a human–robot collaborative assembly line

Cited by 20 publications

References 48 publications

Collaborative robots in manufacturing and assembly systems: literature review and future research agenda

Collaborative robots in manufacturing and assembly systems: literature review and future research agenda

A state-of-the-art on production planning in Industry 4.0

Smart Production Planning Model for T-Shirt Products at Raensa Convection

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