Challenges in Product Lifecycle Management - Evidence from the Automotive Supply Industry

Against the backdrop of a steady shift in value added from the automotive original equipment manufacturers to the automotive suppliers, product lifecycle management in the automotive supply industry gains importance. Prior literature has acknowledged product lifecycle management as paradigm for manufacturing industries, yet little is known about the specific characteristics and boundary conditions in this emerging industry branch. Grounded on extensive empirical evidence from a typical and revelatory case study at a global leader for mechatronic assemblies, this exploratory paper identifies, visualizes, and discusses challenges in product lifecycle management in the automotive supply industry. With the limitation of an exploratory and interpretive single-case study approach, we (1) supply scholars and practitioners with grounded, stakeholder-related insights and (2) link the field of product lifecycle management with information systems

Modeling and Managing Engineering Changes in a Complex Product Development Process

Today\u27s hyper-competitive worldwide market, turbulent environment, demanding customers, and diverse technological advancements force any corporations who develop new products to look into all the possible areas of improvement in the entire product lifecycle management process. One of the areas that both scholars and practitioners have overlooked in the past is Engineering Change Management (ECM). The vision behind this dissertation is to ultimately bridge this gap by identifying main characteristics of a New Product Development (NPD) process that are potentially associated with the occurrence and magnitude of iterations and Engineering Changes (ECs), developing means to quantify these characteristics as well as the interrelationships between them in a computer simulation model, testing the effects of different parameter settings and various coordination policies on project performance, and finally gaining operational insights considering all relevant EC impacts. The causes for four major ECM problems (occurrence of ECs, long EC lead time, high EC cost, and occurrence frequency of iterations and ECs), are first discussed diagrammatically and qualitatively. Factors that contribute to particular system behavior patterns and the causal links between them are identified through the exploratory construction of causal/causal-loop diagrams. To further understand the nature of NPD/ECM problems and verify the key assumptions made in the conceptual causal framework, three field survey studies were conducted in the summer of 2010 and 2011. Information and data were collected to assess the current practice in automobile and information technology industries where EC problems are commonly encountered. ased upon the intuitive understanding gained from these two preparation work, a Discrete Event Simulation (DES) model is proposed. In addition to combining essential project features, such as concurrent engineering, cross functional integration, resource constraints, etc., it is distinct from existing research by introducing the capability of differentiating and characterizing various levels of uncertainties (activity uncertainty, solution uncertainty, and environmental uncertainty) that are dynamically associated with an NPD project and consequently result in stochastic occurrence of NPD iterations and ECs of two different types (emergent ECs and initiated ECs) as the project unfolds. Moreover, feedback-loop relationships among model variables are included in the DES model to enable more accurate prediction of dynamic work flow. Using a numerical example, different project-related model features (e.g., learning curve effects, rework likelihood, and level of dependency of product configuration) and coordination policies (e.g., overlapping strategy, rework review strategy, IEC batching policy, and resource allocation policy) are tested and analyzed in detail concerning three major performance indicators: lead time, cost, and quality, based on which decision-making suggestions regarding EC impacts are drawn from a systems perspective. Simulation results confirm that the nonlinear dynamics of interactions between NPD and ECM plays a vital role in determining the final performance of development efforts

CAE - PROCESS AND NETWORK : A methodology for continuous product validation process based on network of various digital simulation methods

CAE ProNet methodology is to develop CAE network considering interdependencies among digital validations. Utilizing CAE network and considering industrial requirements, an algorithm is applied to execute a product, vehicle development phase, and load case priority oriented CAE process. Major advantage of this research work is to improve quality of simulation results, reducing time-to-market and decreasing dependencies on hardware prototype

Digital Product Innovation in Manufacturing Industries - Towards a Taxonomy for Feedback-driven Product Development Scenarios

In the light of pervasive digitalization, traditional physical products get augmented with digital components that create the potential of making the whole product lifecycle visible for product developers. As numerous opportunities sketch out how feedback such as sensor data might be leveraged for future products, a comprehensive model to describe, particularly a classification model to organize and structure these opportunities seems analytically useful. Hence, this paper pursues a scenario-based approach and proposes a taxonomy for feedback-driven product development scenarios in manufacturing industries. Grounded on (1) empirical data from case studies and focus groups and (2) a systematic literature review, we follow an established taxonomy development method employing the general systems theory as meta-characteristic. With the limitation of a (1) qualitative, interpretive empirical research design and a (2) representative literature review, we contribute to the body of knowledge by shedding light on feedback-driven product development from a classification perspective which may act as structuring and creativity fostering tool

Towards Understanding closed-loop PLM: The Role of Product Usage Data for Product Development enabled by intelligent Properties

Product lifecycle management (PLM) is a strategy of managing a company’s products all the way across their lifecycles. Empowered by new capabilities, intelligent products enable seamless information flow and thus enable closed-loop PLM. Hence, one phenomenon of particular interest is the appreciation of beginning of life activities through middle of life information. Grounded on empirical data from a multiple-case study in three distinct manufacturing industries, we explore this emergent role of product usage data for product development. In detail, we address rationales, opportunities, conditions, and obstacles. Findings indicate that (1) heterogeneous motives drive the exploitation, (2) a positive impact on every product development stage is perceivable, (3) some products and industry ecosystems are more suitable than others, and (4) technical, economic, and social obstacles challenge the exploitation. With the limitation of an interpretive, qualitative research design, our work represents a first step to understand the role of closed-loop PLM

A knowledge sharing framework to support rapid prototyping in collaborative automotive supply chain

In today’s global economy, competition is increasingly driven by a high rate of product renewal. In this context, with market demands for the development of high quality products at lower costs, highly customisable and with short life cycles, new technologies have been adopted by the automotive manufacturers in the move away from a local economy towards the global economy. The continuous evolution of this technology often requires the updating and integration of existing systems within new environments, in order to avoid technological obsolescence. To allow companies to compete in the global market, they (the companies) can no longer be seen acting as standalone entities and are having to reconsider their organisational and operational structure. This thesis presents a Knowledge Sharing Framework Design Roadmap to support rapid prototyping in the automotive and collaborative supply chain. IranKhodro Diesel (IKD) is the automotive company and CarGlass Company (Iran) is the supplier and sponsor of this research study. These two companies will be used to develop and test the Knowledge Sharing Framework Design Roadmap (KSFDR) methodology. An industrially based case study was conducted in IKD and CarGlass to identify key elements in the Knowledge Sharing Framework and provide the focus for this study. The study itself drew on empirical sources of data, including interviews with IKD personnel via an internal company survey. The absence of mechanisms to make information accessible in a multilingual environment and its dissemination to geographically dispersed NPD project team members was identified along with the lack of explicit information about the knowledge used and generated to support first stage rapid prototyping in the product development process with respect to reduction of costs and lead times. The Knowledge Sharing Framework Design Roadmap was tested between IKD and CarGlass. The business objectives in both IKD and CarGlass are the main drivers of knowledge system development. The main novel point from this research study is that this particular framework can be used to capture and disseminate information and knowledge. This was supported by positive feedback from a series of interviews with NPD practitioners. The Knowledge Sharing Framework Design Roadmap (KSFDR) methodology, however, can also be applied in other manufacturing and business environments. Further testing of the framework is strongly advised to minimise any minor flaws, which remain

A new framework for supporting and managing multi-disciplinary system-simulation in a PLM environment

In order to keep products and systems attractive to consumers, developers have to do what they can to meet growing customers’ requirements. These requirements could be direct demands of customers but could also be the consequence of other influences such as globalization, customer fragmentation, product portfolio, regulations and so on. In the manufacturing industry, most companies are able to meet these growing requirements with mechatronic and interdisciplinary designed and developed products, which demand the collaboration between different disciplines. For example, the generation of a virtual prototype and its simulation tools of a mechatronic and multi-disciplinary product or system could require the cooperation of multiple departments within a company or between business partners. In a simulation, a virtual prototype is used for testing a product or a system. This virtual prototype and test approach could be used from the early stages of the development process to the end of the product or system lifecycle. Over years, different approaches/systems to generating virtual prototypes and testing have been designed and developed. But these systems have not been properly integrated, although some efforts have been made with limited success. Therefore, the requirement exists to propose and develop new technologies, methods and methodologies for achieving this integration. In addition, the use of simulation tools requires special expertise for the generation of simulation models, plus the formats of product prototypes and simulation data are different for each system. This adds to the requirements of a guideline or framework for implementing the integration of a multi- and inter- disciplinary product design, simulation software and data management during the entire product lifecycle. The main functionality and metadata structures of the new framework have been identified and optimised. The multi-disciplinary simulation data and their collection processes, the existing PLM (product lifecycle management) software and their applications have been analysed. In addition, the inter-disciplinary collaboration between a variety of simulation software has been analysed and evaluated. The new framework integrates the identified and optimised functionality and metadata structures to support and manage multi- and inter-disciplinary simulation in a PLM system environment. It is believed that this project has made 6 contributions to new knowledge generation: (1) the New Conceptual Framework to Enhance the Support and Management of Multi-Disciplinary System-Simulation, (2) the New System-Simulation Oriented and Process Oriented Data Handling Approach, (3) the Enhanced Traceability of System-Simulation to Sources and Represented Products and Functions, (4) the New System-Simulation Derivation Approach, (5) the New Approach for the Synchronisation of System Describing Structures and (6) the Enhanced System-Simulation Result Data Handling Approach. In addition, the new framework would bring significant benefits to each industry it is applied to. They are: (1) the more effective re-use of individual simulation models in system-simulation context, (2) the effective pre-defining and preparing of individual simulation models, (3) the easy and native reviewable system-simulation structures in relation to input-sources, such as products and / or functions, (4) the easy authoring-software independent update of system-simulation-structures, product-structures and function-structures, (5) the effective, distributed and cohesive post-process and interpretation of system-simulation-results, (6) the effective, easy and unique traceability of the data which means cost reductions in documentation and data security, and (7) the greater openness and flexibility in simulation software interactions with the data holding system. Although the proposed and developed conceptual framework has not been implemented (that would require vast resources), it can be expected that the benefits in 7 above will lead to significant advances in the simulation of new product design and development over the whole lifecycle, offering enormous practical value to the manufacturing industry. Due to time and resource constraints as well as the effort that would be involved in the implementation of the proposed new framework, it is clear there are some limitations to this PhD thesis. Five areas have been identified where further work is needed to improve the quality of this project: (1) an expanded industrial sector and product design and development processes, (2) parameter oriented system and production description in the new framework, (3) the improved user interface design of the new framework, (4) the automatic generation of simulation processes and (5) enhancement of the individual simulation models

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie