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

Data-driven through-life costing to support product lifecycle management solutions in innovative product development

Innovative product usually refers to product that comprises of creativity and new ideas. In the development of such a new product, there is often a lack of historical knowledge and data available to be used to perform cost estimation accurately. This is due to the fact that traditional cost estimation methods are used to predict costs only after a product model has been built, and not at an early design stage when there is little data and information available. In light of this, original equipment manufacturers are also facing critical challenges of becoming globally competitive and increasing demands from customer for continuous innovation. To alleviate these situations this research has identified a new approach to cost modelling with the inclusion of product lifecycle management solutions to address innovative product development.The aim of this paper, therefore, is to discuss methods of developing an extended-enterprise data-driven through-life cost estimating method for innovative product development

Improving root cause analysis through the integration of PLM systems with cross supply chain maintenance data

The purpose of this paper is to demonstrate a system architecture for integrating Product Lifecycle Management (PLM) systems with cross supply chain maintenance information to support root-cause analysis. By integrating product-data from PLM systems with warranty claims, vehicle diagnostics and technical publications, engineers were able to improve the root-cause analysis and close the information gaps. Data collection was achieved via in-depth semi-structured interviews and workshops with experts from the automotive sector. Unified Modelling Language (UML) diagrams were used to design the system architecture proposed. A user scenario is also presented to demonstrate the functionality of the system

A Dynamic Knowledge Management Framework for the High Value Manufacturing Industry

Dynamic Knowledge Management (KM) is a combination of cultural and technological factors, including the cultural factors of people and their motivations, technological factors of content and infrastructure and, where these both come together, interface factors. In this paper a Dynamic KM framework is described in the context of employees being motivated to create profit for their company through product development in high value manufacturing. It is reported how the framework was discussed during a meeting of the collaborating company’s (BAE Systems) project stakeholders. Participants agreed the framework would have most benefit at the start of the product lifecycle before key decisions were made. The framework has been designed to support organisational learning and to reward employees that improve the position of the company in the market place

Global communication part 2: the use of apparel product data management technology

Improving IT communication systems, through the evolution of future PDM applications, is a theme that has received attention due to its perceived benefits in developing global supply chain success factors. This paper discusses the developments and capabilities of such systems, found within global fashion supply chain relationships and environments. Major characteristics identified within the data suggest that PDM technology appears to be improving the speed of data transfer; however, evidence also suggest that the technologies are evolving quicker than consumer understanding, and arguably cost more to implement, train staff and maintain. Nevertheless, PDM technology increases communication efficiency and helps to enhance social economic and corporate development. The article discusses the findings and also presents the issues regarding human interaction; iconography, infrastructure necessity and individual communication enhancements using a variety of technology processes. PDM technology adoption is still a prevalent topic for the long-term developments of global strategy and communication amalgamation

Combining configuration and recommendation to enable an interactive guidance of product line configuration

This paper is interested in e-commerce for complex configurable products/systems. E-commerce makes a wide use of recommendation techniques to help customers identify relevant products or services in large collections of offers. One particular way to achieve this is to offer customers a panel of options among which they can select their preferred ones. A trend in the industry is to go a step further, beyond the selection of pre-defined products from a catalogue by handling products customization. The systems engineering community has shown that, based on product line engineering methods, techniques and tools, it is possible to produce customized products efficiently and at low cost. The problem is that there are usually so many products in a PL that it is impossible to specify all of them explicitly, and therefore traditional recommendation techniques cannot be simply applied. This paper proposes an approach that combines two complementary forms of guidance: configuration and recommendation, to help customers define their own products out of a product line specification. The proposed approach, called interactive configuration supports the combination by organizing the configuration process in a series of partial configurations where decisions are made by the recommendation. This paper illustrates this process by applying it to an example with the content based method for recommendation and the a priori configuration approach

A Smart Products Lifecycle Management (sPLM) Framework - Modeling for Conceptualization, Interoperability, and Modularity

Autonomy and intelligence have been built into many of today’s mechatronic products, taking advantage of low-cost sensors and advanced data analytics technologies. Design of product intelligence (enabled by analytics capabilities) is no longer a trivial or additional option for the product development. The objective of this research is aimed at addressing the challenges raised by the new data-driven design paradigm for smart products development, in which the product itself and the smartness require to be carefully co-constructed. A smart product can be seen as specific compositions and configurations of its physical components to form the body, its analytics models to implement the intelligence, evolving along its lifecycle stages. Based on this view, the contribution of this research is to expand the “Product Lifecycle Management (PLM)” concept traditionally for physical products to data-based products. As a result, a Smart Products Lifecycle Management (sPLM) framework is conceptualized based on a high-dimensional Smart Product Hypercube (sPH) representation and decomposition. First, the sPLM addresses the interoperability issues by developing a Smart Component data model to uniformly represent and compose physical component models created by engineers and analytics models created by data scientists. Second, the sPLM implements an NPD3 process model that incorporates formal data analytics process into the new product development (NPD) process model, in order to support the transdisciplinary information flows and team interactions between engineers and data scientists. Third, the sPLM addresses the issues related to product definition, modular design, product configuration, and lifecycle management of analytics models, by adapting the theoretical frameworks and methods for traditional product design and development. An sPLM proof-of-concept platform had been implemented for validation of the concepts and methodologies developed throughout the research work. The sPLM platform provides a shared data repository to manage the product-, process-, and configuration-related knowledge for smart products development. It also provides a collaborative environment to facilitate transdisciplinary collaboration between product engineers and data scientists