Optimization distribution of activity based costing using agent based technologies

The article describes a distribution of cost with base the activities that will result from the negotiations with the salesmen with base the use agent based technology. The purpose is to solve the optimization problem, taking into account constraints such as the salesmen capacity and income increase in a uniform way and the company’s turnover increase. In this approach a Sales schedule (ABC activity costing) is developed dynamically by all of the concerned participants. The negotiation methodology used allows agents to negotiate with other agents in a certain geographical area based on their sales capacity, commission percentage and the area’s sales turnover. A simulation model based on Repast3 has been developed to evaluate the algorithm accuracy and the system’s convergence. By executing this prototype with various utility functions, interesting results have been achieved showing a convergence in total company’s turnover, salesmen capacity and salesman income.peer-reviewe

Comparative simulation study of production scheduling in the hybrid and the parallel flow

Scheduling is one of the most important decisions in production control. An approach is proposed for supporting users to solve scheduling problems, by choosing the combination of physical manufacturing system configuration and the material handling system settings. The approach considers two alternative manufacturing scheduling configurations in a two stage product oriented manufacturing system, exploring the hybrid flow shop (HFS) and the parallel flow shop (PFS) environments. For illustrating the application of the proposed approach an industrial case from the automotive components industry is studied. The main aim of this research to compare results of study of production scheduling in the hybrid and the parallel flow, taking into account the makespan minimization criterion. Thus the HFS and the PFS performance is compared and analyzed, mainly in terms of the makespan, as the transportation times vary. The study shows that the performance HFS is clearly better when the work stations' processing times are unbalanced, either in nature or as a consequence of the addition of transport times just to one of the work station processing time but loses advantage, becoming worse than the performance of the PFS configuration when the work stations' processing times are balanced, either in nature or as a consequence of the addition of transport times added on the work stations' processing times. This means that physical layout configurations along with the way transport time are including the work stations' processing times should be carefully taken into consideration due to its influence on the performance reached by both HFS and PFS configurations.This work was supported by National Funds through FCT "Fundacao para a Ciencia e a Tecnologia" under the program: PEst2015-2020, ref. UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

Coordination of Supply Webs Based on Dispositive Protocols

A lot of curricula in information systems, also at master level, exists today. However, the strong need in new approaches and new curricula still exists, especially, in European area. The paper discusses the modern curriculum in information systems at master level that is currently under development in the Socrates/Erasmus project MOCURIS. The curriculum is oriented to the students of engineering schools of technical universities. The proposed approach takes into account integration trends in European area as well as the transformation of industrial economics into knowledge-based digital economics The paper presents main characteristics of the proposed curriculum, discuses curriculum development techniques used in the project MOCURIS, describes the architecture of the proposed curriculum and the body of knowledge provided by it

A distributed multi-agent framework for shared resources scheduling

Nowadays, manufacturers have to share some of their resources with partners due to the competitive economic environment. The management of the availability periods of shared resources causes a problem because it is achieved by the scheduling systems which assume a local environment where all resources are on the same site. Therefore, distributed scheduling with shared resources is an important research topic in recent years. In this communication, we introduce the architecture and behavior of DSCEP framework (distributed, supervisor, customer, environment, and producer) under shared resources situation with disturbances. We are using a simple example of manufacturing system to illustrate the ability of DSCEP framework to solve the shared resources scheduling problem in complex systems

Toward smart manufacturing scheduling from an ontological approach of job-shop uncertainty sources

[EN] An integral application of the enabling technologies of Industry 4.0 in the job-shop scheduling problem (JSSP) must contemplate the automation and autonomy of the involved decision-making processes as a goal, which is the main purpose of the smart manufacturing scheduling (SMS) paradigm. In a real production context, uncertainty acts as a barrier that hinders this goal being met and, therefore, any SMS model should integrate uncertainty generators in one way or another. This paper proposes an ontological framework that identifies and structures the entities shaping the joint domain formed by the job-shop scheduling process in its itinerary toward the SMS paradigm, the sources of uncertainty that it faces, and the interrelationship type that link these entities. This ontological framework will serve in future research as a conceptual basis to design new quantitative models that, from a holistic perspective, will address the stochasticity of manufacturing environments and incorporate the management of disturbances into the realtime resolution of automatic and autonomous job-shop scheduling.The research leading to these results received funding from grant RTI2018-101344-B-I00 of MCIN/AEI/10.13039/501100011033 and ¿ERDF A way of making Europe¿, from the Regional Department of Innovation, Universities, Science and Digital Society of the Generalitat Valenciana entitled "Industrial Production and Logistics Optimization in Industry 4.0" (i4OPT) (Ref. PROMETEO/2021/065)", and from the European Union H2020 programs with grant agreements No. 825631 ¿Zero-Defect Manufacturing Platform (ZDMP)¿, No. 872548 "Fostering DIHs for Embedding Interoperability in Cyber-Physical Systems of European SMEs (DIH4CPS)", and No. 958205 ¿Industrial Data Services for Quality Control in Smart Manufacturing (i4Q)¿.Serrano-Ruiz, JC.; Mula, J.; Poler, R. (2022). Toward smart manufacturing scheduling from an ontological approach of job-shop uncertainty sources. IFAC-PapersOnLine. 55(2):150-155. https://doi.org/10.1016/j.ifacol.2022.04.18515015555

Knowledge and agent-based system for decentralised scheduling in manufacturing

The aim of the research paper is to develop algorithms for manufacturers’ agents that would allow them to sequence their own operation plans and to develop a multi-agent infrastructure to allow operation pair agents to cooperatively adjust the timing of manufacturing operations. The scheduling problem consisted of jobs with fixed process plans and of manufacturers collectively offering the necessary operations for the jobs. Manufacturer agents sequenced and pair agents timed each operation as and when required. Timing an operation triggered a cascade of conflicts along the job process plan that other pair agents would pick up on and would take action accordingly. The conventional approach performs conflict resolution in series and manufacturer agents as well as pair agents wait until they are allowed to sequence and time the next operation. The limiting assumption behind that approach was systematically removed, and the proposed approach allowed manufacturers to perform operation scheduling in parallel, cutting down tenfold on the computation time. The multi-agent infrastructure consists of the Protégé knowledge base, the Pellet semantic reasoner and the Workflows and Agent Development Environment (WADE). The case studies used were the MT6, MT10 and LA19 job shop scheduling problems; and an industrial use case was provided to give context to the manufacturing environment investigated. Although there were benefits from the decentralised manufacturing system, we noted an optimality loss of 34% on the makespans. However, for scalability, our approach showed good promise

Design of a Reference Architecture for Production Scheduling Applications based on a Problem Representation including Practical Constraints

Changing customer demands increase the complexity and importance of production scheduling, requiring better scheduling algorithms, e.g., machine learning algorithms. At the same time, current research often neglects practical constraints, e.g., changeovers or transportation. To address this issue, we derive a representation of the scheduling problem and develop a reference architecture for future scheduling applications to increase the impact of future research. To achieve this goal, we apply a design science research approach and, first, rigorously identify the problem and derive requirements for a scheduling application based on a structured literature review. Then, we develop the problem representation and reference architecture as design science artifacts. Finally, we demonstrate the artifacts in an application scenario and publish the resulting prototypical scheduling application, enabling machine learning-based scheduling algorithms, for usage in future development projects. Our results guide future research into including practical constraints and provide practitioners with a framework for developing scheduling applications

Knowledge management technology for integrated decision support systems in process industries

Premi extraordinari doctorat curs 2011-2012, àmbit d’Enginyeria IndustrialNowadays, factors such as globalization of trade, market uncertainty and fierce competition involve dwindling error margins in enterprises. Two key aspects for achieve it are the viability and the competitiveness of enterprises, which highly depend on the effectiveness for taking their decisions related to their manufacturing characteristics, such as economic efficiency, product quality, flexibility or reliability. For this reason, companies have taken the task, for many years, of develop better management information systems in order to help the decision makers to exploit data and models, with the final objective of discussing and improving decision-making. In this sense, decision support systems must be improved in order to deal with the large amount of available data and the heterogeneity of existing modeling approaches along the hierarchical levels in the enterprise structure. Hence, this thesis proposes the application of ontologies as a decision support tool, since they are increasingly seen as a key semantic technology for addressing heterogeneities and mitigating the problems they create and for enabling data mining by semantics-driven the knowledge processing. The aim of this thesis is to contribute to the development of decision support tools for the enterprise process industry. As a decision support tool, must be capable of become a robust model which interacts among the different decision hierarchical levels, providing a unified framework of data and information levels integration. On the other hand, this thesis also aims the improvement in the development of the ontologies. Firstly, a detailed state of the art about the different production process systems, knowledge management base on ontologies, as well as decision support systems is carried out. Based on this review, the specific thesis objectives are posed. Next, a methodology is proposed for the development and use of ontologies, based on the analysis and adaptation of previously existing methodologies. Such methodology is based on the improvement cycle (PSDA), allowing a better way to design, construct and apply domain ontologies. The second part of this thesis is devoted to the application of the different parts of the previously proposed methodology for the development of an ontological framework in the process industry domain concerning the strategic, tactical and operational decision levels. Next, the description of the decision areas in which the ontological framework is applied is presented. Namely, in the process control decision level, the coordination control is considered. Regarding scheduling decisions level, mathematical optimization approaches are applied. Finally, the distributed hierarchical decision level considers the mathematical optimization for decentralized supply chain networks is adopted. These decision areas and the performance of the proposed framework interaction are studied along the different case studies presented in the thesis. On the whole, this thesis represents a step forward toward the integration among the enterprise hierarchical levels, the process and enterprise standardization and improved procedures for decision-making. The aforementioned achievements are boosted by the application of semantic models, which are currently increasingly used.En la actualidad, factores como la globalización del comercio, la incertidumbre del mercado y la feroz competencia implican la disminución de los márgenes de error en las empresas. Dos aspectos claves para lograrlo son la viabilidad y la competitividad de las enterprisesm, que dependen en gran medida la eficacia para la toma de sus decisiones relacionadas con sus características de fabricación, tales como eficiencia económica, la calidad del producto, la flexibilidad y fiabilidad. Por esta razón, las empresas han dado a la tarea, desde hace muchos años, de desarrollar mejores sistemas de gestión de la información con el fin de ayudar a los tomadores de decisiones de explotación de datos y modelos, con el objetivo final de la discusión y mejorar la toma de decisiones. En este sentido, los sistemas de apoyo a las decisiones deben ser mejorados con el fin de hacer frente a la gran cantidad de datos disponibles y la heterogeneidad de los métodos de modelización existentes a lo largo de los niveles jerárquicos en la estructura de la empresa. Por lo tanto, esta tesis se propone la aplicación de ontologías como herramienta de apoyo a la decisión, ya que son cada vez más como una tecnología clave semántica para hacer frente a las heterogeneidades y la mitigación de los problemas que crean y para permitir la extracción de datos por la semántica impulsado la elaboración del conocimiento. El objetivo de esta tesis es contribuir al desarrollo de herramientas de apoyo para la industria de procesos empresariales. Como una herramienta de apoyo a la decisión, debe ser capaz de convertirse en un modelo sólido que interactúa entre los diferentes niveles de decisión jerárquica, proporcionando un marco unificado de datos e integración de los niveles de información. Por otra parte, esta tesis también tiene como objetivo la mejora en el desarrollo del área de ingeniería ontológica. En primer lugar, un estado detallado de la técnica sobre los diferentes sistemas de procesos de producción, la base de la gestión del conocimiento en ontologías, así como los sistemas de soporte de decisiones se ha llevado a cabo. Basado en esa revision, los objetivos específicos de la tesis se plantean. A continuación, se propone una metodología para el desarrollo y uso de ontologías, con base en el análisis y adaptación de las metodologías ya existentes. Dicha metodología se basa en el ciclo de mejora (PSDA), lo que permite una mejor manera de diseñar, construir y aplicar las ontologías de dominio. La segunda parte de esta tesis se dedica a la aplicación de las diferentes partes de la metodología propuesta anteriormente para el desarrollo de un marco ontológico en el ámbito de la industria de procesos relativos a los niveles de decisiones estratégicas, tácticas y operativas. A continuación, la descripción de las áreas de decisión en la que se aplica el marco ontológico se presenta. Es decir, en el nivel de decision de proceso de control, el control de la coordinación se considera. En cuanto al nivel de decisiones de programación de la producción, los métodos matemáticos de optimización se aplican. Finalmente, el nivel jerárquico distribuido decisión considera la optimización matemática de las redes descentralizadas de la cadena de suministro que se adopte. Estas áreas de decisión y el desempeño de la interacción marco propuesto se estudian a lo largo de los diferentes casos de estudio presentados en la tesis. En general, esta tesis supone un paso hacia adelante en la integración entre los niveles jerárquicos de la empresa, el proceso y la estandarización de la empresa y mejorar los procedimientos de toma de decisiones. Los logros mencionados se potencian mediante la aplicación de modelos semánticos, que actualmente se utilizan cada vez más.Award-winningPostprint (published version

Multiagent-Based Model For ESCM

Web based applications for Supply Chain Management (SCM) are now a necessity for every company in order to meet the increasing customer demands, to face the global competition and to make profit. Multiagent-based approach is appropriate for eSCM because it shows many of the characteristics a SCM system should have. For this reason, we have proposed a multiagent-based eSCM model which configures a virtual SC, automates the SC activities: selling, purchasing, manufacturing, planning, inventory, etc. This model will allow a better coordination of the supply chain network and will increase the effectiveness of Web and intel-ligent technologies employed in eSCM software