HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific re... more HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
Flexible workshops are essential components of modern industry, enabling flexible and efficient p... more Flexible workshops are essential components of modern industry, enabling flexible and efficient production. However, to ensure their proper functioning and prevent unexpected breakdowns, it is crucial to monitor their reliability. Production stoppages caused by unforeseen breakdowns can lead to significant financial losses. This chapter proposes to explore the use of Machine Learning (ML) for predicting the reliability of flexible workshops, thus identifying dates for Preventive Maintenance (PM) interventions and optimizing production management. The objectives of this exploration include the presentation of new predictive model developments and the description of ML models capable of predicting workshop reliability based on real-time data, such as equipment monitoring, production data, and maintenance histories. It also aims to identify optimal times for PM interventions, minimizing production disruptions and optimizing resource utilization. Additionally, the chapter will propose cost optimization models to prevent unplanned breakdowns, extend equipment lifespan, optimize spare parts usage, and maximize productivity by avoiding production interruptions and ensuring the smooth operation of the flexible workshop.
The International Journal of Advanced Manufacturing Technology
Industry 4.0 is the basis for the transformation of manufacturing companies into digital enterpri... more Industry 4.0 is the basis for the transformation of manufacturing companies into digital enterprises. It promises more exibility in manufacturing, as well as mass customization, better quality and enhanced productivity. As a result, it empowers companies to meet the challenges of smart manufacturing of increasingly individualized products with shorter time-to-market and improved quality. Smart manufacturing has an important part in Industry 4.0. In ful llment of a need for empirical exploitation, this contribution aims to characterize and analyze a smart manufacturing process of a company specialized in the production of brass accessories, namely the spherical bushels. Basically, we set up a simulation tool to develop a numerical production platform for Industry 4.0 which e ciently operates and manages the production, procurement: through the Material Requirement Planning (MRP, Master Production Program) method, the logistics warehouse and the Cyber-Physical Production System (CPPS). The ndings have been optimized by a new redesigned approach of MRP 2: it is the load-capacity adjustment for the manufacturing planning of a smart workshop and Industry 4.0. Indeed, it is a process of setting up an integrated manufacturing system, which has allowed us to reduce the assembly time of the spherical bushels and to control the production and the assembling process. It allows us to increase the equipment utilization rate by comparing it with the company's equipment before the switch to smart manufacturing. In addition, the optimized results show that the proposed model can signi cantly increase the production e ciency and practical application in Industry 4.0. To the best of our knowledge, this is a rst work addressing the implementation of a simulation platform controlled by a dedicated Cyber-Physical Production System (CPPS) and a Master Production Program. A case study for a company manufacturing brass accessories is presented in this paper. The developed simulation platform present a basis for a future digital twin of the company.
HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific re... more HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
Flexible workshops are essential components of modern industry, enabling flexible and efficient p... more Flexible workshops are essential components of modern industry, enabling flexible and efficient production. However, to ensure their proper functioning and prevent unexpected breakdowns, it is crucial to monitor their reliability. Production stoppages caused by unforeseen breakdowns can lead to significant financial losses. This chapter proposes to explore the use of Machine Learning (ML) for predicting the reliability of flexible workshops, thus identifying dates for Preventive Maintenance (PM) interventions and optimizing production management. The objectives of this exploration include the presentation of new predictive model developments and the description of ML models capable of predicting workshop reliability based on real-time data, such as equipment monitoring, production data, and maintenance histories. It also aims to identify optimal times for PM interventions, minimizing production disruptions and optimizing resource utilization. Additionally, the chapter will propose cost optimization models to prevent unplanned breakdowns, extend equipment lifespan, optimize spare parts usage, and maximize productivity by avoiding production interruptions and ensuring the smooth operation of the flexible workshop.
The International Journal of Advanced Manufacturing Technology
Industry 4.0 is the basis for the transformation of manufacturing companies into digital enterpri... more Industry 4.0 is the basis for the transformation of manufacturing companies into digital enterprises. It promises more exibility in manufacturing, as well as mass customization, better quality and enhanced productivity. As a result, it empowers companies to meet the challenges of smart manufacturing of increasingly individualized products with shorter time-to-market and improved quality. Smart manufacturing has an important part in Industry 4.0. In ful llment of a need for empirical exploitation, this contribution aims to characterize and analyze a smart manufacturing process of a company specialized in the production of brass accessories, namely the spherical bushels. Basically, we set up a simulation tool to develop a numerical production platform for Industry 4.0 which e ciently operates and manages the production, procurement: through the Material Requirement Planning (MRP, Master Production Program) method, the logistics warehouse and the Cyber-Physical Production System (CPPS). The ndings have been optimized by a new redesigned approach of MRP 2: it is the load-capacity adjustment for the manufacturing planning of a smart workshop and Industry 4.0. Indeed, it is a process of setting up an integrated manufacturing system, which has allowed us to reduce the assembly time of the spherical bushels and to control the production and the assembling process. It allows us to increase the equipment utilization rate by comparing it with the company's equipment before the switch to smart manufacturing. In addition, the optimized results show that the proposed model can signi cantly increase the production e ciency and practical application in Industry 4.0. To the best of our knowledge, this is a rst work addressing the implementation of a simulation platform controlled by a dedicated Cyber-Physical Production System (CPPS) and a Master Production Program. A case study for a company manufacturing brass accessories is presented in this paper. The developed simulation platform present a basis for a future digital twin of the company.
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Papers by AYOUB CHAKROUN