Digital transformation in service and computing oriented manufacturing

This volume gathers the peer reviewed papers which were presented at the sixth edition of the International Workshop “Service Orientation in Holonic and Multi-agent Manufacturing—SOHOMA’16” organized on October 6–7, 2016 by the New University of Lisbon, Portugal in collaboration with the CIMR Research Centre in Computer Integrated Manufacturing and Robotics of the University Politehnica of Bucharest, Romania, the LAMIH Laboratory of Industrial and Human Automation Control, Mechanical Engineering and Computer Science of the University of Valenciennes and Hainaut-Cambrésis, France and the CRAN Research Centre for Automatic Control, Nancy of the University of Lorraine, France.info:eu-repo/semantics/publishedVersio

Eco‐Holonic 4.0 Circular Business Model to Conceptualize Sustainable Value Chain Towards Digital Transition

The purpose of this paper is to conceptualize a circular business model based on an Eco-Holonic Architecture, through the integration of circular economy and holonic principles. A conceptual model is developed to manage the complexity of integrating circular economy principles, digital transformation, and tools and frameworks for sustainability into business models. The proposed architecture is multilevel and multiscale in order to achieve the instantiation of the sustainable value chain in any territory. The architecture promotes the incorporation of circular economy and holonic principles into new circular business models. This integrated perspective of business model can support the design and upgrade of the manufacturing companies in their respective industrial sectors. The conceptual model proposed is based on activity theory that considers the interactions between technical and social systems and allows the mitigation of the metabolic rift that exists between natural and social metabolism. This study contributes to the existing literature on circular economy, circular business models and activity theory by considering holonic paradigm concerns, which have not been explored yet. This research also offers a unique holonic architecture of circular business model by considering different levels, relationships, dynamism and contextualization (territory) aspects

Industrial cyber physical systems supported by distributed advanced data analytics

The industry digitization is transforming its business models, organizational structures and operations, mainly promoted by the advances and the mass utilization of smart methods, devices and products, being leveraged by initiatives like Industrie 4.0. In this context, the data is a valuable asset that can support the smart factory features through the use of Big Data and advanced analytics approaches. In order to address such requirements and related challenges, Cyber Physical Systems (CPS) promote the development of more intelligent, adaptable and responsiveness supervisory and control systems capable to overcome the inherent complexity and dynamics of industrial environments. In this context, this work presents an agent-based industrial CPS, where agents are endowed with data analysis capabilities for distributed, collaborative and adaptive process supervision and control. Additionally, to address the different industrial levels’ requirements, this work combines two main data analysis scopes: at operational level, applying distributed data stream analysis for rapid response monitoring and control, and at supervisory level, applying big data analysis for decision-making, planning and optimization. Some experiments have been performed in the context of an electric micro grid where agents were able to perform distributed data analysis to predict the renewable energy production.info:eu-repo/semantics/publishedVersio

Special Session on Industry 4.0

No abstract available

Go-green manufacturing holons: a step towards sustainable manufacturing operations control

Despite their potential benefits in the context of sustainable manufacturing operations, holonic and multi-agent architectures are still not designed methodologically to support this major societal and environmental stake. To fill the gap, the generic concept of go-green manufacturing holon is proposed. The idea is to incite researchers to develop sustainability-oriented manufacturing operations control architectures, being holonic or multi-agents, and to provide them with a usable generic concept easy to appropriate, particularize and implement. An illustration of the concept is proposed as well as its widening in the context of circular economy.Trentesaux, D.; Giret Boggino, AS. (2015). Go-green manufacturing holons: a step towards sustainable manufacturing operations control. Manufacturing letters. 5:29-33. doi:10.1016/j.mfglet.2015.07.003S2933

Dynamic shop floor re-scheduling approach inspired by a neuroendocrine regulation mechanism

[EN] With the development of the market globalisation trend and increasing customer orientation, many uncertainties have entered into the manufacturing context. To create an agile response to the emergence of and change in conditions, this article presents a dynamic shop floor re-scheduling approach inspired by a neuroendocrine regulation mechanism. The dynamic re-scheduling function is the result of cooperation among several autonomous bio-inspired manufacturing cells with computing power and optimisation capabilities. The dynamic re-scheduling model is designed based on hormone regulation principles to agilely respond to the frequent occurrence of unexpected disturbances at the shop floor level. The cooperation mechanisms of the dynamic re-scheduling model are described in detail, and a test bed is set up to simulate and verify the dynamic re-scheduling approach. The results verify that the proposed method is able to improve the performances and enhance the stability of a manufacturing systemThis research was sponsored by the National Natural Science Foundation of China (NSFC) under Grant No. 51175262 and No. 61105114 and the Jiangsu Province Science Foundation for Excellent Youths under Grant BK20121011. This research was also sponsored by the CASES project supported by a Marie Curie International Research Staff Exchange Scheme Fellowship within the 7th European Community Framework Programme under grant agreement No. 294931Zheng, K.; Tang, D.; Giret Boggino, AS.; Gu, W.; Wu, X. (2015). Dynamic shop floor re-scheduling approach inspired by a neuroendocrine regulation mechanism. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture. 229(S1):121-134. https://doi.org/10.1177/0954405414558699S121134229S1Maravelias, C. T., & Sung, C. (2009). Integration of production planning and scheduling: Overview, challenges and opportunities. Computers & Chemical Engineering, 33(12), 1919-1930. doi:10.1016/j.compchemeng.2009.06.007Yandra, & Tamura, H. (2007). A new multiobjective genetic algorithm with heterogeneous population for solving flowshop scheduling problems. International Journal of Computer Integrated Manufacturing, 20(5), 465-477. doi:10.1080/09511920601160288Fattahi, P., & Fallahi, A. (2010). Dynamic scheduling in flexible job shop systems by considering simultaneously efficiency and stability. CIRP Journal of Manufacturing Science and Technology, 2(2), 114-123. doi:10.1016/j.cirpj.2009.10.001Renna, P. (2011). Multi-agent based scheduling in manufacturing cells in a dynamic environment. International Journal of Production Research, 49(5), 1285-1301. doi:10.1080/00207543.2010.518736Qin, L., & Kan, S. (2013). Production Dynamic Scheduling Method Based on Improved Contract Net of Multi-agent. Advances in Intelligent Systems and Computing, 929-936. doi:10.1007/978-3-642-31656-2_128Iwamura, K., Mayumi, N., Tanimizu, Y., & Sugimura, N. (2010). A Study on Real-time Scheduling for Holonic Manufacturing Systems - Application of Reinforcement Learning -. Service Robotics and Mechatronics, 201-204. doi:10.1007/978-1-84882-694-6_35Jana, T. K., Bairagi, B., Paul, S., Sarkar, B., & Saha, J. (2013). Dynamic schedule execution in an agent based holonic manufacturing system. Journal of Manufacturing Systems, 32(4), 801-816. doi:10.1016/j.jmsy.2013.07.004Dan, Z., Cai, L., & Zheng, L. (2009). Improved multi-agent system for the vehicle routing problem with time windows. Tsinghua Science and Technology, 14(3), 407-412. doi:10.1016/s1007-0214(09)70058-6Hsieh, F.-S. (2009). Developing cooperation mechanism for multi-agent systems with Petri nets. Engineering Applications of Artificial Intelligence, 22(4-5), 616-627. doi:10.1016/j.engappai.2009.02.006Tang, D., Gu, W., Wang, L., & Zheng, K. (2011). A neuroendocrine-inspired approach for adaptive manufacturing system control. International Journal of Production Research, 49(5), 1255-1268. doi:10.1080/00207543.2010.518734Keenan, D. M., Licinio, J., & Veldhuis, J. D. (2001). A feedback-controlled ensemble model of the stress-responsive hypothalamo-pituitary-adrenal axis. Proceedings of the National Academy of Sciences, 98(7), 4028-4033. doi:10.1073/pnas.051624198Farhy, L. S. (2004). Modeling of Oscillations in Endocrine Networks with Feedback. Numerical Computer Methods, Part E, 54-81. doi:10.1016/s0076-6879(04)84005-9Cavalieri, S., Macchi, M., & Valckenaers, P. (2003). Journal of Intelligent Manufacturing, 14(1), 43-58. doi:10.1023/a:1022287212706Leitão, P., & Restivo, F. (2008). A holonic approach to dynamic manufacturing scheduling. Robotics and Computer-Integrated Manufacturing, 24(5), 625-634. doi:10.1016/j.rcim.2007.09.005Bal, M., & Hashemipour, M. (2009). Virtual factory approach for implementation of holonic control in industrial applications: A case study in die-casting industry. Robotics and Computer-Integrated Manufacturing, 25(3), 570-581. doi:10.1016/j.rcim.2008.03.020Leitao P. An agile and adaptive holonic architecture for manufacturing control. PhD Thesis, University of Porto, Porto, 2004

Myopia of service-oriented holonic manufacturing systems: the contribution of an observer

Volume 402Service orientation paradigm is particularly well adapted to distributed manu-facturing systems. The difficulty of such systems' production activity control deals with the knowledge management. Indeed, the knowledge is distributed among each entity, which is able to create, modify or communicate them with oth-er entities. As a matter of fact, any entity cannot have a full up-to-date access to all the data of the system. On the shop floor level, a convenient way to implement service oriented manufacturing systems is to rely on the paradigm of Holonic Manufacturing Systems. This paper introduces the possibility of specializing a re-source holon with the objectives to gather the data from the whole holarchy and make these data available to any holon for a decision making. This holon is thus playing the role of a discrete-event observer. After positioning the service-oriented architectures, the HMS reference architecture PROSA is described, especially in terms of decision making. After the decisions were defined, the problematic of on-line decision making in a HMS is described, and a solution of implementation of the observer and of forecasting tools in the architecture is exposed. Finally, two applications are presented, based on an industrial job-shop

Agent-based asset administration shell approach for digitizing industrial assets

Modern manufacturing systems are facing new challenges related to the fast-changing market conditions, increased global competition and rapid technological developments, imposing strong requirements in terms of flexibility, robustness and reconfigurability. In this context, the Industry 4.0 (I4.0) paradigm relies on digitizing industrial assets to fulfil these requirements. The implementation of this digitization process is being promoted by the so-called Asset Administration Shell (AAS), a digital representation of an asset that complies with standardization and interoperability strategies. At this moment, a significant part of the AAS developments is more focused on the information management of the asset along its lifecycle and not concerned with aspects of intelligence and collaboration, which are fundamental aspects to develop I4.0 compliant solutions. In this sense, this paper presents an agent-based AAS approach for enhancing the digitization process of assets, considering agents to embed distributed intelligence and collaborative functions, service orientation to support interoperability, and holonic principles to provide the system organization. The proposed agent-based AAS was implemented in an industrial automation system aiming to analyze its applicability.info:eu-repo/semantics/publishedVersio

An engineering framework for Service-Oriented Intelligent Manufacturing Systems

Nowadays fully integrated enterprises are being replaced by business networks in which each participant provides others with specialized services. As a result, the Service Oriented Manufacturing Systems emerges. These systems are complex and hard to engineer. The main source of complexity is the number of different technologies, standards, functions, protocols, and execution environments that must be integrated in order to realize them. This paper proposes a framework and associated engineering approach for assisting the system developers of Service Oriented Manufacturing Systems. The approach combines multi-agent system with Service Oriented Architectures for the development of intelligentautomation control and execution of manufacturing systems.Giret Boggino, AS.; Garcia Marques, ME.; Botti Navarro, VJ. (2016). An engineering framework for Service-Oriented Intelligent Manufacturing Systems. Computers in Industry. 81:116-127. doi:10.1016/j.compind.2016.02.002S1161278