22,382 research outputs found
Requirements analysis for decision-support system design: evidence from the automotive industry
The purpose of this paper is to outline the requirements analysis that was carried out to support the development of a system that allows engineers to view real-time data integrated from multiple silos such as Product Lifecycle Management (PLM) and Warranty systems, in a single and visual environment. The outcome of this study provides a clear understanding of how engineers working in different phases of the product-lifecycle could utilise such information to improve the decision making process and as a result design better products. This study uses data collected via in-depth semi-structured interviews and workshops that includes people working in various roles within the automotive sector. In order to demonstrate the applicability this approach, SysML diagrams are also provided
Collaborative problem solving within supply chains: general framework, process and methodology
The Problem Solving Process is a central element of the firms' continuous improvement strategies. In this framework, a number of approaches have succeeded to demonstrate their effectiveness to tackle industrial problems. The list includes, but is not limited to PDCA, DMAICS, 7Steps and 8D/9S. However, the emergence and increasing emphasis in the supply chains have impacted the effectiveness of those methods to solve problems that go beyond the boundaries of a single firm and, in consequence, their ability to provide solutions when the contexts on which firms operate are distributed. This can be explained because not only the problems, but also the products, partners, skills, resources and pieces of evidence required to solve those problems are distributed, fragmented and decentralized across the network. This PhD thesis deals with the solving of industrial problems in supply chains based in collaboration. It develops a general framework for studying this paradigm, as well as both a generic process and a collaborative methodology able to deal with the process in practice. The proposal considers all the technical aspects (e.g. products modeling and network structure) and the collaborative aspects (e.g. the trust decisions and/or the power gaps between partners) that simultaneously impact the supply chain operation and the jointly solving of problems. Finally, this research work positions the experiential knowledge as a central lever of the problem solving process to contribute to the continuous improvement strategies at a more global level
Résolution collaborative de problèmes au sein des chaînes logistiques : cadre conceptuel, processus et méthodologie
La Résolution de Problèmes est l'un des piliers des stratégies d'amélioration continue des entreprises. Dans ce cadre, un certain nombre des méthodes ont réussi à démontrer son efficacité pour adresser des problèmes particulièrement complexes. Parmi ces méthodes, on peut distinguer le PDCA, le DMAICS, le 7Steps et le 8D/9S. Pourtant, l'apparition des réseaux distribuées de partenaires, ainsi que le positionnement du concept d'entreprise étendue, ont obligé les entreprises à aller au-delà de ses frontières pour travailler en synergie avec tous les partenaires en amont et en aval de sa chaîne. Dans ce contexte, l'efficacité de ces méthodes de résolution des problèmes a été fortement impactée. Ceci car non seulement les problèmes, mais aussi les produits, les partenaires, les ressources et l'information nécessaires pour sa résolution sont extrêmement fragmentés et décentralisés. Cette thèse s'intéresse donc à la résolution collaborative de problèmes au sein des chaînes distribuées de partenaires et son objectif est de proposer un processus et une méthodologie adaptés à ces contextes. Les propositions faites prennent en compte les aspects techniques (e.g. la modélisation des flux et la configuration de la chaîne) ainsi que les aspects collaboratifs (e.g. le niveau de confiance et/ou le rapport de pouvoir entre les partenaires) que conditionnent l'opération et l'efficacité du réseau. Finalement, cette thèse s'intéresse à l'articulation d'un système de retour d'expérience dans la résolution de problèmes distribués afin d'améliorer son efficacité. ABSTRACT : The Problem Solving Process is a central element of the firms' continuous improvement strategies. In this framework, a number of approaches have succeeded to demonstrate their effectiveness to tackle industrial problems. The list includes, but is not limited to PDCA, DMAICS, 7Steps and 8D/9S. However, the emergence and increasing emphasis in the supply chains have impacted the effectiveness of those methods to solve problems that go beyond the boundaries of a single firm and, in consequence, their ability to provide solutions when the contexts on which firms operate are distributed. This can be explained because not only the problems, but also the products, partners, skills, resources and pieces of evidence required to solve those problems are distributed, fragmented and decentralized across the network. This PhD thesis deals with the solving of industrial problems in supply chains based in collaboration. It develops a general framework for studying this paradigm, as well as both a generic process and a collaborative methodology able to deal with the process in practice. The proposal considers all the technical aspects (e.g. products modeling and network structure) and the collaborative aspects (e.g. the trust decisions and/or the power gaps between partners) that simultaneously impact the supply chain operation and the jointly solving of problems. Finally, this research work positions the experiential knowledge as a central lever of the problem solving process to contribute to the continuous improvement strategies at a more global level
Requirements engineering for computer integrated environments in construction
A Computer Integrated Environment (CIE) is the type of innovative integrated information system that helps to reduce fragmentation and enables the stakeholders to collaborate together in business. Researchers have observed that the concept of CIE has been the subject of research for many years but the uptake of this technology has been very limited because of the development of the technology and its effective implementation. Although CIE is very much valued by both industrialists and academics, the answers to the question of how to develop and how to implement it are still not clear.
The industrialists and researchers conveyed that networking, collaboration, information sharing and communication will become popular and critical issues in the future, which can be managed through CIE systems. In order for successful development of the technology, successful delivery, and effective implementation of user and industry-oriented CIE systems, requirements engineering seems a key parameter. Therefore, through experiences and lessons learnt in various case studies of CIE systems developments, this book explains the development of a requirements engineering framework specific to the CIE system.
The requirements engineering process that has been developed in the research is targeted at computer integrated environments with a particular interest in the construction industry as the implementation field. The key features of the requirements engineering framework are the following: (1) ready-to-use, (2) simple, (3) domain specific, (4) adaptable and (5) systematic, (6) integrated with the legacy systems. The method has three key constructs: i) techniques for requirements development, which includes the requirement elicitation, requirements analysis/modelling and requirements validation, ii) requirements documentation and iii) facilitating the requirements management. It focuses on system development methodologies for the human driven ICT solutions that provide communication, collaboration, information sharing and exchange through computer integrated environments for professionals situated in discrete locations but working in a multidisciplinary and interdisciplinary environment. The overview for each chapter of the book is as follows;
Chapter 1 provides an overview by setting the scene and presents the issues involved in requirements engineering and CIE (Computer Integrated Environments). Furthermore, it makes an introduction to the necessity for requirements engineering for CIE system development, experiences and lessons learnt cumulatively from CIE systems developments that the authors have been involved in, and the process of the development of an ideal requirements engineering framework for CIE systems development, based on the experiences and lessons learnt from the multi-case studies.
Chapter 2 aims at building up contextual knowledge to acquire a deeper understanding of the topic area. This includes a detailed definition of the requirements engineering discipline and the importance and principles of requirements engineering and its process. In addition, state of the art techniques and approaches, including contextual design approach, the use case modelling, and the agile requirements engineering processes, are explained to provide contextual knowledge and understanding about requirements engineering to the readers.
After building contextual knowledge and understanding about requirements engineering in chapter 2, chapter 3 attempts to identify a scope and contextual knowledge and understanding about computer integrated environments and Building Information Modelling (BIM). In doing so, previous experiences of the authors about systems developments for computer integrated environments are explained in detail as the CIE/BIM case studies.
In the light of contextual knowledge gained about requirements engineering in chapter 2, in order to realize the critical necessity of requirements engineering to combine technology, process and people issues in the right balance, chapter 4 will critically evaluate the requirements engineering activities of CIE systems developments that are explained in chapter 3. Furthermore, to support the necessity of requirements engineering for human centred CIE systems development, the findings from semi-structured interviews are shown in a concept map that is also explained in this chapter.
In chapter 5, requirements engineering is investigated from different angles to pick up the key issues from discrete research studies and practice such as traceability through process and product modelling, goal-oriented requirements engineering, the essential and incidental complexities in requirements models, the measurability of quality requirements, the fundamentals of requirements engineering, identifying and involving the stakeholders, reconciling software requirements and system architectures and barriers to the industrial uptake of requirements engineering. In addition, a comprehensive research study measuring the success of requirements engineering processes through a set of evaluation criteria is introduced. Finally, the key issues and the criteria are comparatively analyzed and evaluated in order to match each other and confirm the validity of the criteria for the evaluation and assessment of the requirements engineering implementation in the CIE case study projects in chapter 7 and the key issues will be used in chapter 9 to support the CMM (Capability Maturity Model) for acceptance and wider implications of the requirements engineering framework to be proposed in chapter 8.
Chapter 6 explains and particularly focuses on how the requirements engineering activities in the case study projects were handled by highlighting strengths and weaknesses. This will also include the experiences and lessons learnt from these system development practices. The findings from these developments will also be utilized to support the justification of the necessity of a requirements engineering framework for the CIE systems developments. In particular, the following are addressed.
• common and shared understanding in requirements engineering efforts,
• continuous improvement,
• outputs of requirement engineering
• reflections and the critical analysis of the requirements engineering approaches in these practices.
The premise of chapter 7 is to evaluate and assess the requirements engineering approaches in the CIE case study developments from multiple viewpoints in order to find out the strengths and the weaknesses in these requirements engineering processes. This evaluation will be mainly based on the set of criteria developed by the researchers and developers in the requirements engineering community in order to measure the success rate of the requirements engineering techniques after their implementation in the various system development projects. This set of criteria has already been introduced in chapter 5. This critical assessment includes conducting a questionnaire based survey and descriptive statistical analysis.
In chapter 8, the requirements engineering techniques tested in the CIE case study developments are composed and compiled into a requirements engineering process in the light of the strengths and the weaknesses identified in the previous chapter through benchmarking with a Capability Maturity Model (CMM) to ensure that it has the required level of maturity for implementation in the CIE systems developments. As a result of this chapter, a framework for a generic requirements engineering process for CIE systems development will be proposed.
In chapter 9, the authors will discuss the acceptance and the wider implications of the proposed framework of requirements engineering process using the CMM from chapter 8 and the key issues from chapter 5.
Chapter 10 is the concluding chapter and it summarizes the findings and brings the book to a close with recommendations for the implementation of the Proposed RE framework and also prescribes a guideline as a way forward for better implementation of requirements engineering for successful developments of the CIE systems in the future
Cybersecurity for Manufacturers: Securing the Digitized and Connected Factory
As manufacturing becomes increasingly digitized and data-driven, manufacturers will find themselves at serious risk. Although there has yet to be a major successful cyberattack on a U.S. manufacturing operation, threats continue to rise. The complexities of multi-organizational dependencies and data-management in modern supply chains mean that vulnerabilities are multiplying.
There is widespread agreement among manufacturers, government agencies, cybersecurity firms, and leading academic computer science departments that U.S. industrial firms are doing too little to address these looming challenges. Unfortunately, manufacturers in general do not see themselves to be at particular risk. This lack of recognition of the threat may represent the greatest risk of cybersecurity failure for manufacturers. Public and private stakeholders must act before a significant attack on U.S. manufacturers provides a wake-up call.
Cybersecurity for the manufacturing supply chain is a particularly serious need. Manufacturing supply chains are connected, integrated, and interdependent; security of the entire supply chain depends on security at the local factory level. Increasing digitization in manufacturing— especially with the rise of Digital Manufacturing, Smart Manufacturing, the Smart Factory, and Industry 4.0, combined with broader market trends such as the Internet of Things (IoT)— exponentially increases connectedness. At the same time, the diversity of manufacturers—from large, sophisticated corporations to small job shops—creates weakest-link vulnerabilities that can be addressed most effectively by public-private partnerships.
Experts consulted in the development of this report called for more holistic thinking in industrial cybersecurity: improvements to technologies, management practices, workforce training, and learning processes that span units and supply chains. Solving the emerging security challenges will require commitment to continuous improvement, as well as investments in research and development (R&D) and threat-awareness initiatives. This holistic thinking should be applied across interoperating units and supply chains.National Science Foundation, Grant No. 1552534https://deepblue.lib.umich.edu/bitstream/2027.42/145442/1/MForesight_CybersecurityReport_Web.pd
Making Strategic Supply Chain Capacity Planning more Dynamic to cope with Hyperconnected and Uncertain Environments
Public and private organizations cope with a lot of uncertainties when planning the future of their supply chains. Additionally, the network of stakeholders is now intensely interconnected and dynamic, revealing new collaboration opportunities at a tremendous pace. In such a context, organizations must rethink most of their supply chain planning decision support systems. This is the case regarding strategic supply chain capacity planning systems that should ensure that supply chains will have enough resources to profitably produce and deliver products on time, whatever hazards and disruptions. Unfortunately, most of the existing systems are unable to consider satisfactorily this new deal. To solve this issue, this paper develops a decision support system designed for making strategic supply chain capacity planning more dynamic to cope with hyperconnected and uncertain environments. To validate this decision support system, two industrial experiments have been conducted with two European pharmaceuticals and cosmetics companies
Agent Based Modeling and Simulation Framework for Supply Chain Risk Management
This research develops a flexible agent-based modeling and simulation (ABMS) framework for supply chain risk management with significant enhancements to standard ABMS methods and supply chain risk modeling. Our framework starts with the use of software agents to gather and process input data for use in our simulation model. For our simulation model, we extend an existing mathematical framework for discrete event simulation (DES) to ABMS and then implement the concepts of variable resolution modeling from the DES domain to ABMS and provide further guidelines for aggregation and disaggregation of supply chain models. Existing supply chain risk management research focuses on consumable item supply chains. Since the Air Force supply chain contains many reparable items, we fill this gap with our risk metrics framework designed for reparable item supply chains, which have greater complexity than consumable item supply chains. We present new metrics, along with existing metrics, in a framework for reparable item supply chain risk management and discuss aggregation and disaggregation of metrics for use with our variable resolution modeling
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