A Multi-Stage Remanufacturing Approach for Life Extension of Safety Critical systems

Life extension of safety critical systems is gaining popularity in many industries due to the increasing demand in world's energy consumption and the strong desire to reduce carbon emissions by different countries. Identification and implementation of a suitable life extension strategy enables safety critical systems to perform their intended functions under stated condition for an extended period of time beyond original design life. In the past, the viability analysis of life extension strategies has been undertaken based on the accumulated knowledge and experience of Original Equipment Manufacturer (OEM), maintenance engineers and inspectors. These approaches involving expert judgement are qualitative in nature and based on conservative assumptions, which may lead to inaccurate conclusion or misleading recommendations to asset managers. Therefore, it is crucial to develop an approach consisting of methods to determine the technical condition of components, estimate the cost of life extension interventions and to analyze carbon footprints. “Remanufacturing” is considered as a suitable end-of-life strategy that can help reduce the overall environmental burden from the product by processing waste materials while at the same time keeping reliability high. Due to the advantages of remanufacturing, it is widely applied for life extension purposes in safety critical industries such as offshore oil and gas, nuclear power, petrochemical, renewable energy, rail transport, aviation, shipping, and electricity distribution and transmission. In this paper, a multi-stage approach is presented to analyze the impact of remanufacturing of safety critical systems on the performance of industrial operations in terms of total cost and carbon footprint. In this approach, the equipment health status is determined by modelling the degradation of the system and then the maintenance costs and carbon footprint are calculated. For the purpose of clarity, the proposed model is applied to an air compressor system and the results are discussed

An Internet Based Framework for Micro Devices Assembly

ABSTRACT This paper outlines the design of an Internet based collaborative framework to support the rapid assembly of micro devices. With the help of an agent programming language called 3APL, a distributed approach to achieving the life cycle of the various phases in the assembly of micro devices has been implemented. A discussion of the various agent resources created for a VE oriented approach is also provided in this paper

PROSIS: An isoarchic structure for HMS control

International audienceThis paper presents a holonic and isoarchic approach to the Flexible Manufacturing System (FMS) control. This approach is based on a flat holonic form, where each holon is a model for each entity of the FMS, with a unifying level of communication between holons. After description of this model, called PROSIS, the interaction protocol and decision rules are presented. The objective is to increase the FMS productivity and flexibility, particularly on responsiveness aspects. This responsiveness is achieved through decentralized generation of the production tasks. The reactive behaviour of the FMS control is illustrated by the example of a flexible turning cell, upon occurrence of a failure or of an urgent batch order, and the resulting Gantt charts are shown

Local Digital Twin-based control of a cobot-assisted assembly cell based on Dispatching Rules

In the context of an increasing digitalization of production processes, Digital Twins (DT) are emerging as new simulation paradigm for manufacturing, which leads to potential advances in the production planning and control of production systems. In particular, DT can support production control activities thanks to the bidirectional connection in near real-time with the modeled system. Research on DT for production planning and control of automated systems is already ongoing, but manual and semi-manual systems did not receive the same attention. In this paper, a novel framework focused on a local DT is proposed to control a cobot-assisted assembly cell. The DT replicates the behavior of the cell, providing accurate predictions of its performances in alternative scenarios. Then, building on these predicted estimates, the controller selects, among different dispatching rules, the most appropriate one to pursue different performance objectives. This has been proven beneficial through a simulation assessment of the whole assembly line considered as testbed

Multi-agent based beam search for intelligent production planning and scheduling

Production planning and scheduling is a long standing research area of great practical value, while industrial demand for production planning and scheduling systems is acute. Regretfully, most research results are seldom applied in industry because existing planning and scheduling methods can barely meet the requirements for practical applications. This paper identifies four major requirements, namely generality, solution quality, computation efficiency, and implementation difficulty, for practical production planning and scheduling methods. Based on these requirements, method, a multi-agent based beam search (MABBS), is developed. It seamlessly integrates the multi-agent system (MAS) method and beam search (BS) method into a generic multi-stage multi-level decision making (MSMLDM) model to systematically address all the four requirements within a unified framework. A script language, called EXASL, and an open software platform are developed to simplify the implementation of the MABBS method. For solving complex real-world problems, an MABBS-based prototype production planning, scheduling and execution system is developed. The feasibility and effectiveness of this study is demonstrated with the prototype system and computation experiments. © 2010 Taylor & Francis.postprin

Log Classification in the Hardwood Timber Industry: Method and Value Analysis

RÉSUMÉ : Les industries avec différentes entrées, telles que : l'industrie des produits forestiers (FPI), l'industrie minière ou l'industrie du recyclage, doivent faire face à l'incertitude de matière primaire, ce qui affecte leur capacité à prévoir le rendement de sortie. Pour régler ce problème, les industries peuvent réduire l'incertitude à la source, ou de planifier les opérations en tenant compte de l'incertitude. Dans le FPI, la première approche est généralement utilisée. Par exemple, l'industrie du bois d'œuvre a implémenté des technologies de transformation sophistiquées pour adapter le processus du sciage aux caractéristiques des billes en utilisant la technologie de numérisation pour obtenir des informations précises sur l'état des travaux en cours de fabrication. Une autre approche pour réduire l'incertitude est la classification de matière primaire. Certaines caractéristiques spécifiques peuvent être mesurées à l'entrée pour classer la matière primaire et en conséquence, augmenter la certitude des attentes de production dans chaque classe. Toutefois, si le processus implique les journaux, les minerais des mines ou des papiers recyclés, la classification de matière primaire a une valeur et un coût selon le degré de détail effectué. Cette recherche propose d'abord une méthode basée sur l'analyse des arbres de classification pour classer les billes de feuillus. Ensuite, en utilisant la simulation à base d'agents, nous analysons la valeur des différentes stratégies de classification, de la plus détaillée, à aucune classification. Les résultats montrent dans le cadre de l'industrie du bois de feuillus que l'avantage de classification détaillée est compensé par son coût, tandis qu'une classification relativement simple permet d'améliorer considérablement le rendement de la production.----------ABSTRACT : Industries with variable inputs, such as the forest product industry (FPI), the mining industry or the recycling industry, must cope with material uncertainty, which affects their ability to predict output yields. To deal with this, one can either reduce uncertainty at the source, or plan operations taking uncertainty into account. In the FPI, the first approach is generally used. For instance, the softwood lumber industry has adopted sophisticated transformation technologies that adapt sawing patterns to the log characteristic using scanners technology to acquire accurate information about work-in-process status. Another approach to reduce uncertainty is input material classification. Specific characteristics can be measured to classify input material and therefore reduce uncertainty within each class. However, whether the process involves logs, mining ores or recycled papers, material classification has a value and a cost according to how detailed it is performed. This research first proposes a method based on classification tree analysis to classify hardwood logs. Next, using agent-based simulation, it analyses the value of different classification strategies, from detailed, to no classification at all. Results show in the context of the hardwood lumber industry that the benefit of detailed classification is offset by its cost, while a relatively simple classification dramatically improves output yield. Keywords: hardwood timber industry; material classification; classification tree analysis; agent-based simulation