Comparative Analysis of the Life-Cycle Cost of Robot Substitution: A Case of Automobile Welding Production in China

Zhao, Xiaohong; Wu, Cisheng; Liu, Duan-Yong

doi:10.3390/sym13020226

Cited by 6 publications

(4 citation statements)

References 44 publications

(134 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is used in various contexts, from structuring fixed asset costs in projects to analyzing the current structure of an organization, which enables strategic considerations by managers (Zhao;Wu;Liu, 2021) such as the decision to discontinue a production line or not.…”

Section: Life Cycle Costingmentioning

confidence: 99%

“…Both aim to reduce the cost of ownership of the organization's assets. Although some authors emphasize the strategic connotation of TCO compared to the generalist model of LCC (Gram;Schroeder, 2012;Gu, 2017;Zhao;Wu;Liu, 2021).…”

Section: Total Cost Of Ownershipmentioning

confidence: 99%

“…In terms of the limitations of the method, limiting factors can be highlighted, such as challenges related to obtaining and ensuring the reliability of the data required to operationalize the model, difficulties in implementation and use, and challenges related to the organizational culture of companies adopting a biased perspective for short-term outcomes to the detriment of long-term management decisions (Zhao;Wu;Liu, 2021).…”

Section: Total Cost Of Ownershipmentioning

confidence: 99%

See 2 more Smart Citations

Tools for cost management

Silva,

Leite

2024

Revista PO: R. Eletr. de Eng. de Produção e Correlatas

View full text Add to dashboard Cite

This article aims to provide an overview of the literature in which cost assessment methods are currently used, and their characteristics and limitations are also pointed out. To achieve the proposed objectives, a Systematic Literature Review (RSL) was conducted. It was possible to identify the tools discussed in the bibliographic portfolio studied, namely: life cycle costing, target costing, the total cost of ownership, activity-based costing, variable costing, and mathematical models, as well as the difficulties in implementing these tools in different application contexts. It has also been noted that multiple tools are often employed in integrated methodologies to mitigate the inherent limitations of individual models when treated in isolation. The significance of this article resides in its contribution to the discourse on the evolution of cost management tools and their application within integrated approaches, particularly in addressing the typical challenges encountered in emerging business models.

show abstract

Section: Life Cycle Costingmentioning

confidence: 99%

Section: Total Cost Of Ownershipmentioning

confidence: 99%

Section: Total Cost Of Ownershipmentioning

confidence: 99%

See 1 more Smart Citation

Tools for cost management

Silva,

Leite

2024

Revista PO: R. Eletr. de Eng. de Produção e Correlatas

View full text Add to dashboard Cite

show abstract

“…With the wild application of industrial robots, the research focus on them has shifted to their optimal operations, aiming at the enhancement of sustainable, skilled, and efficient functioning. Welding is a widely employed material joining technology in various industries, such as vehicles, construction machinery, and shipbuilding [3,4]. It involves the heating and fusing of basic materials, making it a prominent manufacturing process.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Considered Process Parameter Optimization of Welding Robots Based on Small Sample Size Dataset

Yan,

Zhang,

2023

Sustainability

View full text Add to dashboard Cite

The welding process is characterized by its high energy density, making it imperative to optimize the energy consumption of welding robots without compromising the quality and efficiency of the welding process for their sustainable development. The above evaluation objectives in a particular welding situation are mostly influenced by the welding process parameters. Although numerical analysis and simulation methods have demonstrated their viability in optimizing process parameters, there are still limitations in terms of modeling accuracy and efficiency. This paper presented a framework for optimizing process parameters of welding robots in industry settings, where data augmentation was applied to expand sample size, auto machine learning theory was incorporated to quantify reflections from process parameters to evaluation objectives, and the enhanced non-dominated sorting algorithm was employed to identify an optimal solution by balancing these objectives. Additionally, an experiment using Q235 as welding plates was designed and conducted on a welding platform, and the findings indicated that the prediction accuracy on different objectives obtained by the enlarged dataset through ensembled models all exceeded 95%. It is proven that the proposed methods enabled the efficient and optimal determination of parameter instructions for welding scenarios and exhibited superior performance compared with other optimization methods in terms of model correctness, modeling efficiency, and method applicability.

show abstract