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Applying additive manufacturing technologies to a supply chain: A Petri net-based decision model

Patalas-Maliszewska Justyna, Wiśniewski Remigiusz, Zhou MengChu, Topczak Marcin, Wojnakowski Marcin

International Journal of Applied Mathematics and Computer Science

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2024

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Vol. 34, no. 3

513--525

EN

Nowadays, applying additive manufacturing (AM) technologies into a supply chain (SC) permits realization of the so-called “demand chains” and transformation of conventional production to mass customization. However, integration of AM technologies within an SC indicates the need to support managers’ decision about such an investment. Therefore, this work develops a Petri net-based decision support model that determines the changes in an SC by adopting AM and improving customer-perceived value (CPV), based on a case study regarding a real-life metal production process. The basis for building such a model is the supply chain operation reference model (SCOR), focusing on CPV, due to the need for redesigning the SC starting from the customer instead of the company. To achieve the research objective, this work introduces a novel verification methodology for a Petri net-based decision model. The research results show that applying the developed model, which is based on the selected characteristics of the production process and parameters describing the potential integration of AM within the SC, allows managers to perceive a scenario in the form of graphical models about positive or negative impacts of introducing AM into the SC. The managers find the Petri net-based decision support model presented in this paper a beneficial tool to support the implementation of changes in an SC and show the potential increase in customer satisfaction thanks to the integration of AM within an SC.

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Design optimization of the Petri net-based production process supported by additive manufacturing technologies

Patalas-Maliszewska Justyna, Wiśniewski Remigiusz, Topczak Marcin, Wojnakowski Marcin

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2022

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Vol. 70, nr 2

art. no. e140693

EN

In the era of smart manufacturing and Industry 4.0, the rapid development of modelling in production processes results in the implementation of new techniques, such as additive manufacturing (AM) technologies. However, large investments in the devices in the field of AM technologies require prior analysis to identify the possibilities of improving the production process flow. This paper proposes a new approach to determine and optimize the production process flow with improvements made by the AM technologies through the application of the Petri net theory. The existing production process is specified by a Petri net model and optimized by AM technology. The modified version of the system is verified and validated by the set of analytic methods safeguarding against the formal errors, deadlocks, or unreachable states. The proposed idea is illustrated by an example of a real-life production process.

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Assessment of the possibility of using Bayesian nets and Petri nets in the process of selecting additive manufacturing technology in a manufacturing company

Topczak Marcin, Śliwa Małgorzata

Applied Computer Science

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2021

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Vol. 17, no 1

5--16

EN

The changes caused by Industry 4.0 determine the decisions taken by manufacturing companies. Their activities are aimed at adapting processes and products to dynamic market requirements. Additive manufacturing technologies (AM) are the answer to the needs of enterprises. The implementation of AM technology brings many benefits, although for most 3D printing techniques it is also relatively expensive. Therefore, the implementation process should be preceded by an appropriate analysis, in order, finally, to assess the solution. This article presents the concept of using the Bayesian network when planning the implementation of AM technology. The use of the presented model allows the level of the success of the implementation of selected AM technology, to be estimated under given environmental conditions.

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Model oceny poziomu ryzyka w przedsiębiorstwie produkcyjnym

Topczak Marcin, Patalas-Maliszewska Justyna

Zarządzanie Przedsiębiorstwem

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2019

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Vol. 22, nr 4

14--21

EN

Risk is an inherent element of business operations. In the case of production enterprises, the risk can be considered in the area of material, machine, man and process organization. PN ISO 31000:2018 recommends integrating the risk management system with other management systems within a company, pointing to the significant role of understanding the external and internal context of the organization and identifying the needs of stakeholders. The risk management process consists of two steps: identification and analysis affecting the risk factors and quantitative measurement of its level. The article proposes a risk management model for a production enterprise, making a theoretical analysis. The proposed model and procedure are based on the guidelines of PN ISO 31000:2018. The proposed procedure for risk management includes the stage of hazard identification in a selected area, setting criteria and levels of admissibility of individual threats, risk analysis and evaluation of risk levels in relation to the adopted criteria.