A Holistic Algorithm for Materials Requirement Planning in Collaborative Networks

[EN] Collaboration has increasingly been considered a key topic within the small and medium-sized enterprises, allowing dealing with the intense competitiveness of today¿s globalised markets. The European H2020 Cloud Collaborative Manufacturing Networks Project proposes mechanisms to encourage collaboration among enterprises, through the computation of collaborative plans. Particularly, this paper focuses on the proposal of a holistic algorithm to deal with the automated and collaborative calculation of the Materials Requirement Plan. The proposed algorithm is validated in a collaborative network belonging to the automotive industry.The research leading to these results is in the frame of the “Cloud Collaborative Manufacturing Networks” (C2NET) project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 636909.Andres, B.; Poler, R.; Sanchis, R. (2017). A Holistic Algorithm for Materials Requirement Planning in Collaborative Networks. IFIP Advances in Information and Communication Technology. 560:41-50. https://doi.org/10.1007/978-3-319-65151-4_4S4150560CORDIS Europa: Factories of the Future. H2020-EU.2.1.5.1. - Technologies for Factories of the Future (2014)H2020 Project C2NET (2015). http://cordis.europa.eu/project/rcn/193440_en.htmlAndres, B., Sanchis, R., Poler, R.: A cloud platform to support collaboration in supply networks. Int. J. Prod. Manag. Eng. 4(1), 5–13 (2016)Andres, B., Sanchis, R., Lamothe, J., Saari, L., Hauser, F.: Integrated production-distribution planning optimization models: a review in collaborative networks context. Int. J. Prod. Manag. Eng. 5(1), 31–38 (2017)Camarinha-Matos, L.M., Afsarmanesh, H.: Collaborative networks: a new scientific discipline. J. Intell. Manuf. 16(4–5), 439–452 (2005)Andres, B., Poler, R.: Models, guidelines and tools for the integration of collaborative processes in non-hierarchical manufacturing networks: a review. Int. J. Comput. Integr. Manuf. 2(29), 166–201 (2016)Sanchis, R., Poler, R., Lario, F.C.: Identification and analysis of Disruptions: the first step to understand and measure Enterprise Resilience. In: International Conference on Industrial Engineering and Engineering Management, pp. 424–431 (2012)Andres, B., Saari, L., Lauras, M., Eizaguirre, F.: Optimization algorithms for collaborative manufacturing and logistics processes. In: Zelm, M., Doumeingts, G., Mendonça, J.P. (eds.) Enterprise Interoperability in the Digitized and Netwroked Factory of the Future, iSTE 2016, pp. 167–173 (2016)Orbegozo, A., Andres, B., Mula, J., Lauras, M., Monteiro, C., Malheiro, M.: An overview of optimization models for integrated replenishment and production planning decisions. In: Building Bridges Between Researchers and Practitioners. Book of Abstracts of the International Joint Conference CIO-ICIEOM-IISE-AIM (IJC 2016), p. 68 (2016

A MILP for multi-machine injection moulding sequencing in the scope of C2NET Project

[EN] The goal of C2NET European H2020 Funded Project is the creation of cloud-enabled tools for supporting the SMEs supply network optimization of manufacturing and logistic assets based on collaborative demand, production and delivery plans. In the scope of C2NET Project, and particularly in the Optimisation module (C2NET OPT), this paper proposes a novel holistic mixed integer linear programing (MILP) model to optimise the injection sequencing in a multi-machine case. The results of the MILP will support the production planner decision-making process in the calculation of (i) moulds setup in certain machines, and (ii) the amount of products to produce in order to minimise the setup, inventory, and backorders costs. The designed MILP takes part of the algorithms repository created in C2NET European Funded Project to solve realistic industry planning problems. The MILP is verified in realistic data considering three data sets with different sizes, in order to test it’s the computation efficiency.European Union's Horizon research and innovation programmeAndrés Navarro, B.; Sanchis, R.; Poler, R.; Díaz-Madroñedo, M.; Mula, J. (2018). A MILP for multi-machine injection moulding sequencing in the scope of C2NET Project. International Journal of Production Management and Engineering. 6(1):29-36. https://doi.org/10.4995/ijpme.2018.8913SWORD29366

A Proposal of Standardised Data Model for Cloud Manufacturing Collaborative Networks

[EN] The growing amount of data to be handled by collaborative networks raises the need of introducing innovative solutions to fulfil the lack of affordable tools, especially for Small and Medium-Sized Enterprises, to manage and exchange data. The European H2020 Project Cloud Collaborative Manufacturing Networks develops and offers a structured data model, called Standardised Tables, as an organised framework to jointly work with existing databases to manage big data collected from different industries belonging to the CNs. The information of the Standardised Tables will be mainly used with optimisation and collaboration purposes. The paper describes an application of the Standardised Tables in one of the pilots of the aforementioned project, the automotive industry pilot, for solving the collaborative problem of a Materials Requirement Plan.The research leading to these results is in the frame of the “Cloud Collaborative Manufacturing Networks” (C2NET) project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 636909.Andres, B.; Sanchis, R.; Poler, R.; Saari, L. (2017). A Proposal of Standardised Data Model for Cloud Manufacturing Collaborative Networks. IFIP Advances in Information and Communication Technology. 560:77-85. https://doi.org/10.1007/978-3-319-65151-4_7S7785560Andres, B., Poler, R.: Models, guidelines and tools for the integration of collaborative processes in non-hierarchical manufacturing networks: a review. Int. J. Comput. Integr. Manuf. 2(29), 166–201 (2016)Zikopoulos, P., Eaton, C.: Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. McGraw-Hill Osborne Media, New York (2011)Zhou, B., Wang, S., Xi, L.: Data model design for manufacturing execution system. J. Manuf. Technol. Manag. 16(8), 909–935 (2005)Steven, W.: Getting the MES model – methods for system analysis. ISA Trans. 35(2), 95–103 (1996)Reda, A.: Extracting the extended entity-relationship model from a legacy relational database. Inf. Syst. 28(6), 597–618 (2003)Teorey, T.J., Yang, D., Fry, J.P.: A logical design methodology for relational database using the extended entity-relationship model. ACM Comput. Surv. 18(2), 197–222 (1986)Victor, M., Arie, S.: Representing extended entity-relationship structures in relational databases: a modular approach. ACM Trans. Database Syst. 17(3), 423–464 (1992)CORDIS Europa, Factories of the Future, H2020-EU.2.1.5.1. - Technologies for Factories of the Future (2014)H2020 Project C2NET (2015). http://cordis.europa.eu/project/rcn/193440_en.htmlAndres, B., Sanchis, R., Poler, R.: A cloud platform to support collaboration in supply networks. Int. J. Prod. Manag. Eng. 4(1), 5–13 (2016)APICS, “SCOR Framework,” Supply Chain Operations Reference model (SCOR) (2017)Orbegozo, A., Andres, B., Mula, J., Lauras, M., Monteiro, C., Malheiro, M.: An overview of optimization models for integrated replenishment and producction planning decisions. In: Building Bridges Between Researchers and Practitioners. Book of Abstracts of the International Joint Conference CIO-ICIEOM-IISE-AIM (IJC2016), p. 68 (2016)Andres, B., Poler, R., Saari, L., Arana, J., Benaches, J.V., Salazar, J.: Optimization models to support decision-making in collaborative networks: a review. In: Building Bridges Between Researchers and Practitioners. Book of Abstracts of the International Joint Conference CIO-ICIEOM-IISE-AIM (IJC2016), p. 70 (2016)Andres, B., Sanchis, R., Lamothe, J., Saari, L., Hauser, F.: Combined models for production and distribution planning in a supply chain. In: Building Bridges Between Researchers and Practitioners. Book of Abstracts of the International Joint Conference CIO-ICIEOM-IISE-AIM (IJC2016), p. 71 (2016

Development of a mapping system engineering approaches to classic product development processes of technical products: A work project of project management in product development

Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementThe automotive industry faces the challenge of meeting customer requirements while ensuring technological advancements, fast and cost-effective development, and high-quality production. Information systems play a crucial role in efficiently designing internal processes and meeting customer demands. Personalized solutions are increasingly adopted to cater to individual preferences while maintaining up-to-date technology. Information systems are utilized to record and manage customer requirements, optimize production processes, control inventories, and facilitate effective communication between departments. Product data management (PDM) solutions are widely employed, with 77% of automotive companies implementing them. PDM encompasses the storage and management of data relevant to product development, supporting the entire product lifecycle. As product complexity grows, efficient management of product data becomes essential, along with the optimization of business processes to shorten development time and parallelize tasks. CAx coordination, involving computer-aided design (CAD), manufacturing (CAM), and engineering (CAE), ensures smooth communication and coordination across the product development process. PDM systems act as intermediaries between CAx coordination and enterprise resource planning systems, facilitating seamless integration of design and manufacturing processes. Leading providers of enterprise resource planning and CAD systems offer software solutions for product lifecycle management and PDM, enabling centralized and accessible product information, streamlining development and management processes

Survey on Additive Manufacturing, Cloud 3D Printing and Services

Cloud Manufacturing (CM) is the concept of using manufacturing resources in a service oriented way over the Internet. Recent developments in Additive Manufacturing (AM) are making it possible to utilise resources ad-hoc as replacement for traditional manufacturing resources in case of spontaneous problems in the established manufacturing processes. In order to be of use in these scenarios the AM resources must adhere to a strict principle of transparency and service composition in adherence to the Cloud Computing (CC) paradigm. With this review we provide an overview over CM, AM and relevant domains as well as present the historical development of scientific research in these fields, starting from 2002. Part of this work is also a meta-review on the domain to further detail its development and structure

A framework for co-designing product and production system to support resource-efficient manufacturing

This thesis reports on research undertaken to investigate how to advance the current practices of resource efficiency and sustainability consideration in manufacturing business through the simultaneous design of Product and Production System (P&PS). The primary objective of this research is the development of a framework and methods to support a manufacturer to transform the current independent design processes into a single design process facilitating designs of resource-efficient P&PS. [Continues.

Desenvolvimento de equipamento de manipulação de objectos deformáveis e a sua interacção com uma máquina de injecção de plásticos

In this project, our objective was to thoroughly investigate the feasibility of automating a process at Ficocables by integrating a robotic arm. Specifically, we focused on automating the joining of two separate processes while eliminating the need for manual intervention in the second operation. The equipment involved in the process includes a Roboco Zamak injection machine and a Babyplast polymer injection machine. With well-defined project requirements, we explored various solutions and sought guidance from Fluidotronica, a renowned expert in this domain. With their support, we identified the collaborative robot JAKA Zu 3s, equipped with a long-finger gripper, as the optimal solution for our needs. To assess the financial viability, we conducted a meticulous financial analysis using methods like NPV and payback period, both of which demonstrated promising results. Although the implementation of the robotic arm is still pending, the outcomes of our study highlight its remarkable versatility for future applications within Ficocables. This project exemplifies the potential advantages of automation and offers valuable insights for forthcoming initiatives in this field.Neste projeto, o objetivo era investigar exaustivamente a viabilidade de automatizar um processo na Ficocables através da integração de um braço robótico. Especificamente, concentrámo-nos em automatizar a junção de dois processos separados, eliminando a necessidade de intervenção manual na segunda operação. O equipamento envolvido no processo inclui uma máquina de injeção de Zamak, denominada Robocop e uma máquina de injeção de polímero denominada Babyplast. Com os requisitos de projeto bem definidos, explorámos várias soluções e procurámos orientação junto da Fluidotronica, um especialista de renome neste domínio. Com o seu apoio, identificámos o robô colaborativo JAKA Zu 3s, equipado com uma pinça de dedos longos como a solução ideal para as necessidades deste projeto. Para avaliar a viabilidade financeira, efetuou-se uma análise financeira meticulosa utilizando métodos como o NPV e o período de retorno do investimento, tendo ambos demonstrado resultados promissores. Embora a implementação do braço robótico ainda esteja pendente, os resultados do nosso estudo destacam a sua notável versatilidade para futuras aplicações na Ficocables. Este projeto exemplifica as vantagens potenciais da automatização e oferece uma visão valiosa para iniciativas futuras neste domínio

A Novel MILP Model for the Production, Lot Sizing, and Scheduling of Automotive Plastic Components on Parallel Flexible Injection Machines with Setup Common Operators

[EN] In this article, a mixed integer linear program (MILP) model is proposed for the production, lot sizing, and scheduling of automotive plastic components to minimize the setup, inventory, stockout, and backorder costs, by taking into account injection molds as the main index to schedule on parallel flexible injection machines. The proposed MILP considers the minimum and maximum inventory capacities and penalizes stockout. A relevant characteristic of the modeled problem is the dependence between mold setups to produce plastic components. The lot sizing and scheduling problem solution results in the assignment of molds to machines during a specific time period and in the calculation of the number of components to be produced, which is often called lot size, following a sequence-dependent setup time. Depending on the machine on which the mold is setup, the number of units to be produced will be distinct because machines differ from one another. The stock coverage, defined in demand days, is also included in the MILP to avoid backorders, which is highly penalized in the automotive supply chain. Added to this, the proposed model is extended by considering setup common operators to respond to and fulfill the constraints that appear in automotive plastic enterprises. In this regard, the MILP presented solves a lot-sizing and scheduling problem, emerged in a second-tier supplier of a real automotive supply chain. Finally, this article validates the MILP by performing experiments with different sized instances, including small, medium, and large. The large-sized dataset is characterized by replicating the amount of data used in the real enterprise, which is the object of this study. The goodness of the model is evaluated with the computational time and the deviation of the obtained results as regards to the optimal solution.Thiis work was supported by the Conselleria de Educacion, Investigacion, Cultura y Deporte-Generalitat Valenciana for hiring predoctoral research staff with Grant no. ACIF/2018/170 and European Social Fund with Grant Operational Program of FSE 2014-2020, the Valencian Community, and the authors would like to acknowledge the support of the researchers participating in the collaborative projects 'Cloud Collaborative Manufacturing Networks' (C2NET) (http://c2net-project.eu/), which has received funding from the EU Horizon 2020 Research and Innovation Programme with grant agreement no. 63690, and "Zero Defects Manufacturing Platform" (ZDMP) (http://www.zdmp.eu), which has received funding from the EU Horizon 2020 Research and Innovation Programme with grant agreement no. 825631.Andres, B.; Guzmán-Ortiz, BE.; Poler, R. (2021). A Novel MILP Model for the Production, Lot Sizing, and Scheduling of Automotive Plastic Components on Parallel Flexible Injection Machines with Setup Common Operators. Complexity. 2021:1-16. https://doi.org/10.1155/2021/6667516116202

Data-driven through-life costing to support product lifecycle management solutions in innovative product development

Innovative product usually refers to product that comprises of creativity and new ideas. In the development of such a new product, there is often a lack of historical knowledge and data available to be used to perform cost estimation accurately. This is due to the fact that traditional cost estimation methods are used to predict costs only after a product model has been built, and not at an early design stage when there is little data and information available. In light of this, original equipment manufacturers are also facing critical challenges of becoming globally competitive and increasing demands from customer for continuous innovation. To alleviate these situations this research has identified a new approach to cost modelling with the inclusion of product lifecycle management solutions to address innovative product development.The aim of this paper, therefore, is to discuss methods of developing an extended-enterprise data-driven through-life cost estimating method for innovative product development