Dimitris Kiritsis

Closed-loop PLM for intelligent products in the era of the Internet of things

Abstract With the advent of the information and related emerging technologies, such as RFID, small size sensors and sensor networks or, more generally, product embedded information devices (PEID), a new generation of products called smart or intelligent products is available in the market. Although various definitions of intelligent products have been proposed, we introduce a new definition of the notion of Intelligent Product inspired by what happens in nature with us as human beings and the way we develop intelligence and knowledge. We see an intelligent product as a product system which contains sensing, memory, data processing, reasoning and communication capabilities at four intelligence levels. This future generations of Intelligent Products will need new Product Data Technologies allowing the seamless interoperability of systems and exchange of not only Static but of Dynamic Product Data as well. Actual standards for PDT cover only lowest intelligence of today’s products. In this context, we try to shape the actual state and a possible future of the Product Data Technologies from a Closed-Loop Product Lifecycle Management (C-L PLM) perspective. Our approach is founded in recent findings of the FP6 IP 507100 project PROMISE and follow-up research work. Standards of the STEP family, covering the product lifecycle to a certain extend (PLCS) as well as MIMOSA and ISO 15926 are discussed together with more recent technologies for the management of ID and sensor data such as EPCglobal, OGC-SWE and relevant PROMISE propositions for standards. Finally, the first efforts towards ontology based semantic standards for product lifecycle management and associated knowledge management and sharing are presented and discussed.

Research issues on product lifecycle management and information tracking using smart embedded systems

Abstract PROMISE will develop appropriate technology, including product lifecycle models, product embedded information devices with associated firmware and software components and tools for decision making based on data gathered through a product lifecycle. This is done to enable and exploit the seamless flow, tracing and updating of information about a product, after its delivery to the customer and up to its final destiny (deregistration, decommissioning) and back to the designer and producer. The breakthrough contribution of PROMISE, in the long term, is to allow information flow management to go beyond the customer, to close the product lifecycle information loops, and to enable the seamless e-transformation of product lifecycle information to knowledge. The PROMISE R&D implementation plan includes fundamental and applied research activities in the disciplines of information systems modelling, smart embedded systems, short and long distance wireless communication technologies, data management and modelling, design for X and adaptive production management for beginning of life (BOL), statistical methods for predictive maintenance for middle of life (MOL) and planning and management of product end of life (EOL). After a general description of the PROMISE project, we present an example of the issues to be addressed in it. It consists of defining a data structure for recording maintainability data during the maintenance operations in order to use them in design for maintainability.

Research issues on closed-loop PLM

This study introduces the research issues on closed-loop product lifecycle management (PLM) where product information flow is closed due to emerging technologies. PLM is a new strategic approach to manage the product lifecycle information efficiently over the whole product lifecycle. Recently, with emerging technologies, PLM enables us to gather and analyze the product lifecycle information and make decisions on several issues without spatial and temporal constraints. However, the PLM system just provides us with new opportunities to gain the competitiveness. To remove ineffectiveness within the product lifecycle and maximize the advantage of closed-loop PLM, it is necessary to look into new challenging issues. For this purpose, first, we introduce the concept of closed-loop PLM. Then, we explore several research problems that become highlighted in the closed-loop PLM. For each product lifecycle phase, we introduce research issues with the review of their previous research and address the requirements for resolving them. Finally, we close with discussion about our work and introduction of further research issues.

Product lifecycle management – from its history to its new role

This paper is a result of comprehensive consultation among the authors, with the scientists and leading actors in the area of PLM, which is a reference term for a list of phenomena currently ongoing in the industrial community. This paper discusses the pervasive concept of product lifecycle management (PLM), starting from its history to its constituent elements and its role in the current industry. The authors propose and elaborate their vision for the future steps of the PLM in terms of emerging issues and topics that industrial practitioners and researchers need to address.

An ontology-based approach for Product Lifecycle Management

Ontologies are rapidly becoming popular in various research fields. There is a tendency both in converting existing models into ontologies and in creating new models. In this work we are focusing on Closed-Loop Product Lifecycle Management (PLM) models. An ontology model of a Product Data and Knowledge Management Semantic Object Model for PLM has been developed, with the aim of implementing ontology advantages and features into the model. An initial effort of developing the model into an ontology using Web Ontology Language-Description Logic (OWL-DL) is described in detail and the background and the motives for converting existing PLM models to ontologies is provided. The new model facilitates several of the OWL-DL capabilities, while maintaining previously achieved characteristics. Furthermore, a case study is presented based on application scenarios on the automotive industry. This case study deals with data integration and interoperability problems, in which a significant number of reasoning capabilities is implemented.

A review of knowledge-based expert systems for process planning. Methods and problems

This paper presents a review of knowledge-based expert systems for process planning and related methods and problems. It is based mainly on literature and partially on a questionnaire investigation carried out by the author. After a general presentation of process planning, the main problems are classified and the related methods and approaches for solving them are discussed. Finally, a list of fifty-two prototype systems is presented and their main characteristics are summarised in two tables.

A framework for RFID applications in product lifecycle management

This study introduces an overall framework for radio frequency identification (RFID) applications in product lifecycle management (PLM). Recently, with emerging technologies related to product identification and wireless mobile tele-communication, PLM provides a new environment that enables lifecycle actors to gather and analyse product lifecycle information, and make efficient decisions without spatial and temporal constraints. However, previous research has paid little attention to how to apply the emerging technologies into PLM. To cope with this limitation, in the current study, RFID applications in PLM are dealt with from technical and business viewpoints. To this end, an overall framework for RFID applications in PLM is proposed. It contains the definition of a product embedded information device (PEID) that uses RFID technology, its specification and operation scenarios for each application. Furthermore, application issues and their overall procedures are introduced for each lifecycle phase.

A multi-objective evolutionary algorithm for EOL product recovery optimization: turbocharger case study

Recently, the importance of the end-of-life (EOL) product recovery process has been rising since the return rate of products is increasing due to strict environmental regulations on products and economic reasons. In addition to this, the advent of emerging product identification technologies makes product lifecycle data visible at EOL phase. In this regard, the optimization of product recovery processes becomes highlighted as a challenging issue of EOL. At the inspection phase after disassembly, each part can have various EOL recovery options such as re-use, remanufacturing, and disposal. Depending on the selected EOL options of parts, the recovery value of an EOL product will be different. Hence, it is essential to develop a decision-making method that can select the best EOL options of parts for maximizing the recovery value of an EOL product. Although some previous works have focused on improving EOL operations, there has been a lack of research which dealt with EOL product recovery optimization in a quantitative manner. To cope with this limitation, in this study, we focus on a selection problem of EOL product recovery options for a turbocharger case, for maximizing its recovery value which includes both recovery cost and quality. To solve the problem efficiently, we develop a multi-objective evolutionary algorithm (MOEA). To show the effectiveness of our algorithm, we carry out computational experiments.

Multicriteria decision-aid approach for product end-of-life alternative selection

The selection of the best compromise alternative for treating a product at its end of life (EOL) is presented. Each EOL alternative has its own consequences from an economical, environmental and social point of view. The criteria used to determine these consequences are often contradictory and not equally important. In the presence of multiple conflicting criteria, an optimal EOL alternative rarely exists. Hence, the decision-maker should seek the best compromise EOL alternative. The present paper proposes a multicriteria decision-aid (MCDA) approach to aid the decision-maker in selecting the best compromise EOL alternative on the basis of his/her preferences and the performances of EOL alternatives with respect to the relevant environmental, social and economic criteria. This approach is important because it allows the user to consider various conflicting criteria simultaneously and it takes into account his/her preferences. The paper analyses the most important aspects of this approach such as the constitution of a set of EOL alternatives, the selection of a list of relevant criteria to evaluate the EOL alternatives and the choice of an appropriate multicriteria decision-aid method. A case study is provided to illustrate how the proposed approach can be used for product EOL alternative selection in real-world applications.

A generic Petri net model for dynamic process planning and sequence optimization

Abstract In this paper a Petri net based approach for dynamic process planning and sequencing is presented. By following the proposed method it is possible to: (1) represent manufacturing knowledge of the type of precedence relations constraints, (2) represent dynamically the process planning procedure itself, (3) produce and simulate all possible process-planning solutions (process plans) and (4) find alternative optimized solutions by applying simple manufacturing heuristics. The proposed method is based on the construction of an original dynamic Petri net model upon which reachability analysis is performed and a reachability tree is automatically created. Depth-first search algorithms are then applied upon the reachability tree and all possible paths (process plans) can be calculated. Manufacturing heuristics may help to reduce the volume of big original reachability trees and optimum alternative solutions may be calculated by applying optimization criteria.