Developing an Agent Based Heuristic Optimisation System for Complex Flow Shops with Customer-Imposed Production Disruptions

The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems. However, unpredictable disruptions, such as change in sequence of order, order cancellation and change in production delivery due time, imposed by customers on flow-shops that impact production processes and inventory control call for a more adaptive approach capable of responding to these changes. In this research work, a new adaptive framework and agent-based heuristic optimization system was developed to investigate the disruption consequences and recovery strategy. A case study using an Original Equipment Manufacturer (OEM) production process of automotive parts and components was adopted to justify the proposed system. The results of the experiment revealed significant improvement in terms of total number of late orders, order delivery time, number of setups and resources utilization, which provide useful information for manufacturer’s decision-making policies.

Product descriptions as Programs: a Case Study

The company in this case study manufactures furniture for ships. This business sector is characterized by a high degree of customization. One way of handling the various products is to have a separate product description for each variant. Experience shows that this results in a large number of different product descriptions, in one company as many as 40,000. As the number of different descriptions increases, it becomes easier to create a new description than it is to search for an existing description, thus exacerbating the problem. Therefore, the company in the case study placed great importance on keeping the product descriptions to a minimum, but without limiting the variability. We were able to offer a solution. Based on previous research, we have implemented a system for the company whereby product structures are described by means of computer programs instead of using the traditional bill of material structure. This method of defining generic product descriptions makes it possible to handle variability without increasing the number of descriptions. In theory, this highly structured method should offer a better solution if the users manage to program the product descriptions. The idea of this research was to see if the more complex solution also worked in practice

Developing agent based heuristic optimization system for complex flow shop with customer-imposed production disruptions

The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems.However, unpredictable disruptions, such as change in sequence of order, order cancellation and change in production delivery due time, imposed by customers on flow-shops that impact production processes and inventory control call for a more adaptive approach capable of responding to these changes.In this research work, a new adaptive framework and agent-based heuristic optimization system was developed to investigate the disruption consequences and recovery strategy. A case study using an Original Equipment Manufacturer (OEM) production process of automotive parts and components was adopted to justify the proposed system.The results of the experiment revealed significant improvement in terms of total number of late orders, order delivery time, number of setups and resources utilization, which provide useful information for manufacturer’s decision-making policies

Developing Agent Based Heuristic Optimisation System for Complex Flow Shops with Customer-Imposed Production Disruptions

The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems. However, unpredictable disruptions, such as change in sequence of order, order cancellation and change in production delivery due time, imposed by customers on flow-shops that impact production processes and inventory control call for a more adaptive approach capable of responding to these changes. In this research work, a new adaptive framework and agent-based heuristic optimization system was developed to investigate the disruption consequences and recovery strategy. A case study using an Original Equipment Manufacturer (OEM) production process of automotive parts and components was adopted to justify the proposed system. The results of the experiment revealed significant improvement in terms of total number of late orders, order delivery time, number of setups and resources utilization, which provide useful information for manufacturers decision-making policies

Developing agent based heuristic optimisation system for complex flow shops with customer-imposed production distruptions

The study of complex manufacturing flow-shops has seen a number of approaches and frameworks proposed to tackle various production-associated problems. However, unpredictable disruptions, such as change in sequence of order, order cancellation and change in production delivery due time, imposed by customers on flow-shops that impact production processes and inventory control call for a more adaptive approach capable of responding to these changes. In this research work, a new adaptive framework and agent-based heuristic optimization system was developed to investigate the disruption consequences and recovery strategy. A case study using an Original Equipment Manufacturer (OEM) production process of automotive parts and components was adopted to justify the proposed system. The results of the experiment revealed significant improvement in terms of total number of late orders, order delivery time, number of setups and resources utilization, which provide useful information for manufacturer’s decision-making policies

Variant-oriented Planning Models for Parts/Products Grouping, Sequencing and Operations

This research aims at developing novel methods for utilizing the commonality between part/product variants to make modern manufacturing systems more flexible, adaptable, and agile for dealing with less volume per variant and minimizing total changes in the setup between variants. Four models are developed for use in four important domains of manufacturing systems: production sequencing, product family formation, production flow, and products operations sequences retrieval. In all these domains, capitalizing on commonality between the part/product variants has a pivotal role. For production sequencing; a new policy based on setup similarity between product variants is proposed and its results are compared with a developed mathematical model in a permutation flow shop. The results show the proposed algorithm is capable of finding solutions in less than 0.02 seconds with an average error of 1.2%. For product family formation; a novel operation flow based similarity coefficient is developed for variants having networked structures and integrated with two other similarity coefficients, operation and volume similarity, to provide a more comprehensive similarity coefficient. Grouping variants based on the proposed integrated similarity coefficient improves changeover time and utilization of the system. A sequencing method, as a secondary application of this approach, is also developed. For production flow; a new mixed integer programing (MIP) model is developed to assign operations of a family of product variants to candidate machines and also to select the best place for each machine among the candidate locations. The final sequence of performing operations for each variant having networked structures is also determined. The objective is to minimize the total backtracking distance leading to an improvement in total throughput of the system (7.79% in the case study of three engine blocks). For operations sequences retrieval; two mathematical models and an algorithm are developed to construct a master operation sequence from the information of the existing variants belonging to a family of parts/products. This master operation sequence is used to develop the operation sequences for new variants which are sufficiently similar to existing variants. Using the proposed algorithm decreases time of developing the operations sequences of new variants to the seconds

Set-Based Prototyping in the Context of the Configurable Virtual Product: The Construction of the Learning Value Streams (LVS) Model

RÉSUMÉ La présente thèse de doctorat est le résultat de sept années de recherche intervention dans les domaines de la conception et du développement de produits suivant le paradigme lean en aérospatial. Cette recherche action est motivée par la nécessité de développer les connaissances ainsi que les outils appropriés pour le développement de produits suivant l’approche lean (LPD pour Lean Product Development) et en particulier celle de l’ « ingénierie concourante fondée sur les options de conception » (SBCE pour Set-Based Concurrent Engineering) en aérospatial. Une telle nécessité se justifie par les facteurs socioéconomiques du 21ème siècle qui imposent des approches de conception et développement toujours plus robustes, résilientes, réactives, flexibles, innovantes et adaptables face aux fluctuations du marché et à la demande des consommateurs qui évolue rapidement, ceci afin de permettre aux compagnies de demeurer compétitives. L’objectif principal de la recherche, au vue de tels impératifs, est d’identifier, pour ensuite développer et intégrer dans un modèle holistique, les aspects, les caractéristiques et les catalyseurs essentiels des approches LPD et SBCE appliquées à l’industrie aérospatiale de façon à supporter l’implémentation à grande échelle de telles approches, et ce, dans une optique sousjacente de gestion de cycle de vie du produit (PLM pour Product Lifecycle Management). La planification et l’exécution du projet de recherche sont réalisées en respectant une méthodologie éprouvée en conception (DRM pour Design Research Methodology) afin de focaliser les résultats sur l’avancement des connaissances et de la pratique du LPD et SBCE en tant qu’approches de conception. La recherche apporte en conséquence des contributions majeures à ces champs d’étude tout en prescrivant une méthodologie de transformation des processus et outils de développement de produits dans l’industrie par le biais de l’implémentation du modèle de « chaines de valeur apprenantes » (LVS pour Learning Value Streams). Plus en détails, les contributions aux avancées scientifiques et pratiques dans le domaine vont comme suit : (1) La proposition d’un nouveau cadre d’analyse de la littérature SBCE, ainsi qu’une méthodologie de revue systématique fondée sur des données probantes; (2) L’avancement des connaissances théoriques et pratiques du LPD et SBCE des aspects les plus généraux aux plus significatifs; (3) L’avancement des connaissances théoriques et pratiques sur la modélisation et les structures de produit requises dans une optique de gestion de cycle de vie du produit----------ABSTRACT The work reported in this thesis is the result of seven years of participatory action research in the field of Lean Product Development (LPD) in aerospace engineering. This research is motivated by the necessity to develop understanding and support for practical implementations of lean product development and especially Set-Based Concurrent Engineering (SBCE) in industry. Such necessity is justified by 21st century compelling socioeconomic factors that demand robust, resilient, responsive, flexible, innovative, adaptable and lean product development processes in order for companies to stay competitive in rapidly changing markets. The main purpose of the research is to identify and develop the essential SBCE and LPD aspects, characteristics, features and catalysts as they relate to aerospace large-scale industrial product development in order to form a holistic model that can support practical implementations of LPD in industry from a product lifecycle perspective. A design research methodology (DRM) is used for planning and executing the design research project while ensuring that focus is placed on achieving progress with regards to understanding and implementation of SBCE and LPD as Design practices. As a result, this thesis work provides substantial contribution to understanding of LPD and SBCE and furthermore, entails valuable proposal for the practice in industry through the CCS model and the construction of the Learning Value Streams (LVS) model. Major contributions to the advancement of scientific knowledge and practice in the fields are as follows: (1) The proposal of a new SBCE dual analysis framework combined with an evidence-based systematic review methodology; (2) The advancement of theoretical and practical understanding of LPD and SBCE from the larger to the most significant aspects; (3) The advancement of theoretical and practical understanding of product models and product structure progression requirements for lean product lifecycle management; (4) the proposal of a new methodology, including new as-tested structure to support cross-collaboration during prototyping and testing in lifecycle management contexts; (5) The proposal of a new existential domain alongside the functional, technological and physical domains in order to address the lack of product modelling constructs and methodology when it comes to service or as-tested configurations, hardware testing transactions and prototype information tracking on the basis o

An effective tool for supply chain decision support during new product development process

The global marketplace has transformed supply chain design into a discipline which requires business sense supported by mathematical expertise. Several methods have been introduced to support supply chain design, most notably mixed integer programming. The current methods are tailor-made for situations where a product's bill-of-material is fixed. However, this assumption does not hold during product development where several competing product designs exist. Therefore this research investigates the question of what is an effective way to support supply chain decisions during new product development. The study is divided into four research questions, corresponding to the articles from which the dissertation is compiled: (1) Does a product structure-driven method exist for modeling and analyzing supply chains? (2) If such a method is discovered, what is its mathematical formulation? (3) Is there evidence to support the theoretical and practical usability of such a method? (4) How can strategic supply chain decisions be validated? Regarding question (1) the research finds that there is a shortage of methods that fulfill supply chain modeling and analysis requirements imposed by new product development process. During the research a Petri-net based method was constructed which satisfies these requirements. For question (2), the formal definitions of the constructed Petri net class are provided. Regarding question (3), the research finds that the created method and associated tool are useful aids when solving the question of the effect of demand variation and the number of product variants on the optimal supply chain. Furthermore, interviews with end users of the tool implementation provide evidence of the Petri net method's practical usefulness. Regarding question (4), the research finds that the validation of strategic supply chain decisions from companies' reporting systems is important, but it has not become a common practice due to the challenges in integrating various IT systems

Gestão de Riscos Logísticos em Cadeias de Suprimentos: Otimização via Metamodelo de Simulação.

Alguns tipos de riscos podem causar danos às cadeias de suprimentos, provocando rupturas nos fluxos de materiais e produtos acabados. Riscos logísticos se relacionam às falhas nos processos de transporte, armazenagem, produção e vendas. A gestão adequada desses riscos é fator crítico para a integração dos fluxos sob a responsabilidade da logística e operações, cujas atividades são frequentemente realizadas por provedores de serviços logísticos. Entretanto, observou-se a falta de procedimentos sistemáticos focados na gestão de riscos logísticos que melhor aproveitasse as vantagens da integração entre métodos de simulação e otimização. A pesquisa foi realizada em uma cadeia de suprimentos do segmento automotivo português, a partir de dados secundários disponíveis na literatura. Os problemas desse estudo foram: (a) quais os impactos dos riscos logísticos sobre o desempenho dessa cadeia? (b) sob a influência desses riscos, que ajustes no sistema logístico poderiam melhorar a resposta do arranjo aos impactos? Para solucionar tais questões, definiu-se como objetivo, mitigar os efeitos desses riscos a partir de um metamodelo de simulação para a otimização de parâmetros críticos. As atividades logísticas desempenhadas na cadeia de suprimentos foram escolhidas como objeto de estudo. Essa pesquisa foi classificada como aplicada, quantitativa e exploratória normativa, considerando, respectivamente, a sua natureza, a abordagem do problema e os objetivos. A simulação a eventos discretos, elaborada no ambiente Arena®, foi utilizada como método de pesquisa. A otimização Black Box, realizada através do software OptQuest®, foi empregada para projetar os parâmetros adequados para o sistema logístico. Um metamodelo de regressão baseado no método OLS foi desenvolvido a partir da projeção e implantação de experimentos, servindo para integrar as saídas do modelo de simulação às entradas do modelo de otimização. Inúmeras técnicas de verificação e validação foram empregadas para calibrar o modelo de otimização via simulação, tais como: implantação modular e análise de sensibilidade. Uma sistemática metodológica fundamentada na abordagem DMAIC foi elaborada para relacionar as etapas de gestão dos riscos logísticos e conduzir aos resultados dessa pesquisa, incluindo a identificação (Definir), avaliação (Mensuração), gestão (Melhoria e análise) e monitoramento (Controle) do risco logístico. Um evento de risco logístico foi inserido no modelo com o fim de reproduzir rupturas no fluxo físico de distribuição e permitir a avaliação dos seus impactos sobre o desempenho da cadeia. Os impactos foram medidos por meio do custo logístico total, do risco de ruptura e da taxa de nível de serviço. Estratégias de mitigação do risco logístico de transporte, como redundância e flexibilidade, foram testadas para minimizar simultaneamente custo e risco e maximizar a taxa de entrega. A solução sugerida pelo modelo multiobjetivo de otimização via simulação mostrou ser adequada e eficaz já que os ajustes no sistema logístico bloquearam as consequências da ruptura. A principal contribuição da pesquisa foi desenvolver procedimentos sistemáticos para melhorar a gestão de riscos logísticos no âmbito de cadeias de suprimentos a partir do uso combinado entre métodos de simulação e otimização

The LOFAR Transients Pipeline

Current and future astronomical survey facilities provide a remarkably rich opportunity for transient astronomy, combining unprecedented fields of view with high sensitivity and the ability to access previously unexplored wavelength regimes. This is particularly true of LOFAR, a recently-commissioned, low-frequency radio interferometer, based in the Netherlands and with stations across Europe. The identification of and response to transients is one of LOFAR's key science goals. However, the large data volumes which LOFAR produces, combined with the scientific requirement for rapid response, make automation essential. To support this, we have developed the LOFAR Transients Pipeline, or TraP. The TraP ingests multi-frequency image data from LOFAR or other instruments and searches it for transients and variables, providing automatic alerts of significant detections and populating a lightcurve database for further analysis by astronomers. Here, we discuss the scientific goals of the TraP and how it has been designed to meet them. We describe its implementation, including both the algorithms adopted to maximize performance as well as the development methodology used to ensure it is robust and reliable, particularly in the presence of artefacts typical of radio astronomy imaging. Finally, we report on a series of tests of the pipeline carried out using simulated LOFAR observations with a known population of transients.Comment: 30 pages, 11 figures; Accepted for publication in Astronomy & Computing; Code at https://github.com/transientskp/tk