Knowledge-based Engineering in Product Development Processes - Process, IT and Knowledge Management perspectives

Product development as a field of practice and research has significantly changed due to the general trends of globalization changing the enterprise landscapes in which products are realized. The access to partners and suppliers with high technological specialization has also led to an increased specialization of original equipment manufacturers (OEMs). Furthermore, the products are becoming increasingly complex with a high functional and technological content and many variants. Combined with shorter lifecycles which require reuse of technologies and solutions, this has resulted in an overall increased knowledge intensity which necessitates a more explicit approach towards knowledge and knowledge management in product development. In parallel, methods and IT tools for managing knowledge have been developed and are more accessible and usable today. One such approach is knowledge-based engineering (KBE), a term that was coined in the mid-1980s as a label for applications which automate the design of rule-driven geometries. In this thesis the term KBE embraces the capture and application of engineering knowledge to automate engineering tasks, regardless of domain of application, and the thesis aims at contributing to a wider utilization of KBE in product development (PD). The thesis focuses on two perspectives of KBE; as a process improvement IT method and as a knowledge management (KM) method. In the first perspective, the lack of explicit regard for the constraints of the product lifecycle management (PLM) architecture, which governs the interaction of processes and IT in PD, has been identified to negatively affect the utilization of KBE in PD processes. In the second perspective, KM theories and models can complement existing methods for identifying potential for KBE applications.Regarding the first perspective, it is concluded that explicit regard for the PLM architecture decreases the need to develop and maintain software code related to hard coded redundant data and functions in the KBE application. The concept of service oriented architecture (SOA) has been found to enable an the explicit regard for the PLM architecture.. Regarding the second perspective, it is concluded that potential for KBE applications is indicated by: 1.) application of certain types of knowledge in PD processes 2.) high maturity and formalization of the applied knowledge 3.) a codification strategy for KM and 4.) an agreement and transparency regarding how the knowledge is applied, captured and transferred. It is also concluded that the formulation of explicit KM strategies in PD should be guided by knowledge application and its relation to strategic objectives focusing on types of knowledge, their role in the PD process and the methods and tools for their application. These, in turn, affect the methods and tools deployed for knowledge capture in order for it to integrate with the processes of knowledge origin. Finally, roles and processes for knowledge transfer have to be transparent to assure the motivation of individuals to engage in the KM strategy

Knowledge-based Engineering in Product Development Processes - Process, IT and Knowledge Management perspectives

Product development as a field of practice and research has significantly changed due to the general trends of globalization changing the enterprise landscapes in which products are realized. The access to partners and suppliers with high technological specialization has also led to an increased specialization of original equipment manufacturers (OEMs). Furthermore, the products are becoming increasingly complex with a high functional and technological content and many variants. Combined with shorter lifecycles which require reuse of technologies and solutions, this has resulted in an overall increased knowledge intensity which necessitates a more explicit approach towards knowledge and knowledge management in product development. In parallel, methods and IT tools for managing knowledge have been developed and are more accessible and usable today. One such approach is knowledge-based engineering (KBE), a term that was coined in the mid-1980s as a label for applications which automate the design of rule-driven geometries. In this thesis the term KBE embraces the capture and application of engineering knowledge to automate engineering tasks, regardless of domain of application, and the thesis aims at contributing to a wider utilization of KBE in product development (PD). The thesis focuses on two perspectives of KBE; as a process improvement IT method and as a knowledge management (KM) method. In the first perspective, the lack of explicit regard for the constraints of the product lifecycle management (PLM) architecture, which governs the interaction of processes and IT in PD, has been identified to negatively affect the utilization of KBE in PD processes. In the second perspective, KM theories and models can complement existing methods for identifying potential for KBE applications.Regarding the first perspective, it is concluded that explicit regard for the PLM architecture decreases the need to develop and maintain software code related to hard coded redundant data and functions in the KBE application. The concept of service oriented architecture (SOA) has been found to enable an the explicit regard for the PLM architecture.. Regarding the second perspective, it is concluded that potential for KBE applications is indicated by: 1.) application of certain types of knowledge in PD processes 2.) high maturity and formalization of the applied knowledge 3.) a codification strategy for KM and 4.) an agreement and transparency regarding how the knowledge is applied, captured and transferred. It is also concluded that the formulation of explicit KM strategies in PD should be guided by knowledge application and its relation to strategic objectives focusing on types of knowledge, their role in the PD process and the methods and tools for their application. These, in turn, affect the methods and tools deployed for knowledge capture in order for it to integrate with the processes of knowledge origin. Finally, roles and processes for knowledge transfer have to be transparent to assure the motivation of individuals to engage in the KM strategy

Knowledge-Based Engineering supported by the Digital-Twin: the case of the Power Transformer at EFACEC

Industry 4.0 has made it possible for emerging technologies to revolutionize how organizations operate. New applications, supported by the Internet of things, cyber physical systems, and cloud computing, take advantage of large data exchange networks that capture data from the real and virtual world, to generate valuable insights for product development. This, together with the growing digitalization of product lifecycle information, has made information the most valuable asset of an organization, as it can be applied to improve product design, reduce lead time and decrease monetary costs. However, the growing volume, formats, and purposes of the information an organization captures, also brings challenges for information management, and consequently, appropriate IM and KM instruments and strategies must be adopted to successfully take advantage of organizational knowledge. The adoption of Knowledge-based Engineering can accomplish these goals. KBE refers to the knowledge management tasks of capturing, storing, modeling, coding, and sharing of organizational knowledge, both in explicit form, such as documents, and tacit form, present in the minds of employees. Ultimately, this results in systems that can automate design tasks. Also in the context of technological advances, a new concept called Digital Twin has emerged, which employs bidirectional data transmission to mirror the lifecycle of a physical product, in the virtual realm. Proposed DT functionalities actively use organizational knowledge to improve and automate product design, and as such, this technology can be an adequate vessel for KBE. This dissertation focuses on the implementation of the Digital Twin in power transformer development processes. Using the case of Efacec, a portuguese firm of the energy sector, the DT concept was developed, and this involved defining functionalities that are driven by organizational knowledge to automate, optimize, and streamline PT design tasks, thus accomplishing the goal of KBE. Some of the proposed DT features are the generation of design templates, the identification of design non-conformities, and the capture of engineer feedback. Furthermore, the DT information architecture that is required for these functionalities to successfully be implemented, was envisioned, by defining all captured and generated information in each PT lifecycle phase. Finally, a faceted classification scheme that classifies DT information and enables queries within the DT platform, was developed

Exchange of knowledge in customized product development processes

If Customized Product Development is perceived as developing products that fulfill the customers individual requirements and in parallel reflect production constraints, such as manufacturing capabilities, a direct demand can be derived for solutions to adapt a given design easy and fast to new requirements based upon the companies production knowledge - at best in an automated way. The latter is usually covered by Knowledge Based Engineering systems. KBE systems are capable to automate repetitive engineering tasks, such as the automated calculation of ship structural design. However, while the efficiency of implemented KBE projects is non controversial, the development or modification of an existing KBE solution usually requires substantial investments due to knowledge acquisition, codification and software implementation. In addition most solutions are still case based and not grounded in structural frameworks. Knowledge is often written in a proprietary language; rules and algorithms are not compatible with other KBE-frameworks and are usually not on a level that is comprehensible for the engineers or domain experts. While this may not be crucial for long development cycles, it may become a hurdle in terms of Customized Product Development with its short cycles. In other words, future KBE must support an incorporation of knowledge from different domains and business units. Thus the objective of the paper is to explain the need for a change in collaborative knowledge sharing and re-use in context of KBE. Based upon, the constraints for a KBE related interchange format are drafted. A three layered approach is proposed in order to adequately represent and exchange KBE knowledge. Each layer addresses different levels of abstraction: an upper layer describing just the core knowledge at a glance, a middle layer in order to codify the knowledge on abstract level, but with purpose of software development and a base layer covering the software code itself. Utilizing an independent format for management of KBE knowledge, the users of CAx systems are able to exchange codified knowledge and gain the rationale behind. Hence the full paper attempts to deliver a substantial contribution for the development of systems, which are capable to easily adapt a given design to upcoming user-requirements, while facing the production challenges

A new knowledge sourcing framework to support knowledge-based engineering development

New trends in Knowledge-Based Engineering (KBE) highlight the need for decoupling the automation aspect from the knowledge management side of KBE. In this direction, some authors argue that KBE is capable of effectively capturing, retaining and reusing engineering knowledge. However, there are some limitations associated with some aspects of KBE that present a barrier to deliver the knowledge sourcing process requested by the industry. To overcome some of these limitations this research proposes a new methodology for efficient knowledge capture and effective management of the complete knowledge life cycle. Current knowledge capture procedures represent one of the main constraints limiting the wide use of KBE in the industry. This is due to the extraction of knowledge from experts in high cost knowledge capture sessions. To reduce the amount of time required from experts to extract relevant knowledge, this research uses Artificial Intelligence (AI) techniques capable of generating new knowledge from company assets. Moreover the research reported here proposes the integration of AI methods and experts increasing as a result the accuracy of the predictions and the reliability of using advanced reasoning tools. The proposed knowledge sourcing framework integrates two features: (i) use of advanced data mining tools and expert knowledge to create new knowledge from raw data, (ii) adoption of a well-established and reliable methodology to systematically capture, transfer and reuse engineering knowledge. The methodology proposed in this research is validated through the development and implementation of two case studies aiming at the optimisation of wing design concepts. The results obtained in both use cases proved the extended KBE capability for fast and effective knowledge sourcing. This evidence was provided by the experts working in the development of each of the case studies through the implementation of structured quantitative and qualitative analyses

Digitised engineering knowledge for prefabricated façades

Façade design is a multidisciplinary activity requiring the balancing of many conflicting design requirements. Very often, however, the designed façade does not respond to these requirement, as relevant design and manufacturing knowledge, normally originating downstream in the design process, is not properly used upstream in the process. The inability to respond to this challenge increases the environmental impact of the construction sector, which is currently covering nearly 40% of the global emissions. Also, improving the stagnant sector’s productivity is of paramount importance today, as it is deemed to be nearly as half as that of the manufacturing sector. This research has thus investigated ways to collect, store, represent and digitalise the engineering knowledge that underpins the design of façade products for façades that are better designed. The work has involved a close collaboration with the British general contractor (and façade manufacturer) Laing O’Rourke. The research has explored ways of using design and manufacturing knowledge and it has developed a digital tool and tested its functionalities. In the first part, after a review of the state-of-the-art in knowledge-based approaches in other fields, the digital tool, and relevant methodology, are developed. The tool informs the user about the expected performance and manufacturability of the façade product under analysis. The boundaries of traditional research were also pushed beyond the proof-of-concept by validating the digital tool in both simulated and real-world scenarios. The goal was to understand how people can develop a design solution while being supported by a digital tool. It was found that using such tool increases the user’s awareness about the consequences of the his/her choices in less time. In the last part of the research, the tool was used to develop a novel optimisation algorithm, by including considerations about aesthetics and manufacturability, in parallel with the traditional performance-based approach. The application of the algorithm to a case study has shown that it is possible to improve existing solutions in terms of performance, without affecting aesthetic and manufacturability significantly.EPSRC, Laing O'Rourk

Powertrain Assembly Lines Automatic Configuration Using a Knowledge Based Engineering Approach

Technical knowledge and experience are intangible assets crucial for competitiveness. Knowledge is particularly important when it comes to complex design activities such as the configuration of manufacturing systems. The preliminary design of manufacturing systems relies significantly on experience of designers and engineers, lessons learned and complex sets of rules and is subject to a huge variability of inputs and outputs and involves decisions which must satisfy many competing requirements. This complicated design process is associated with high costs, long lead times and high probability of risks and reworks. It is estimated that around 20% of the designer’s time is dedicated to searching and analyzing past available knowledge, while 40% of the information required for design is identified through personally stored information. At a company level, the design of a new production line does not start from scratch. Based on the basic requirements of the customers, engineers use their own knowledge and try to recall past layout ideas searching for production line designs stored locally in their CAD systems [1]. A lot of knowledge is already stored, and has been used for a long time and evolved over time. There is a need to retrieve this knowledge and integrate it into a common and reachable framework. Knowledge Based Engineering (KBE) and knowledge representation techniques are considered to be a successful way to tackle this design problem at an industrial level. KBE is, in fact, a research field that studies methodologies and technologies for capturing and re-using product and process engineering knowledge to achieve automation of repetitive design tasks [2]. This study presents a methodology to support the configuration of powertrain assembly lines, reducing design times by introducing a best practice for production systems provider companies. The methodology is developed in a real industrial environment, within Comau S.p.A., introducing the role of a knowledge engineer. The approach includes extraction of existing technical knowledge and implementation in a knowledge-based software framework. The macro system design requirements (e.g. cycle time, production mix, etc.) are taken as input. A user driven procedure guides the designer in the definition of the macro layout-related decisions and in the selection of the equipment to be allocated within the project. The framework is then integrated with other software tools allowing the first phase design of the line including a technical description and a 2D and 3D CAD line layout. The KBE application is developed and tested on a specific powertrain assembly case study. Finally, a first validation among design engineers is presented, comparing traditional and new approach and estimating a cost-benefit analysis useful for future possible KBE implementations

Knowledge-Based Design Patterns for Detailed Ship Structural Design

For detailed ship structural design standardization is a means to ensure a consistent build quality and to reduce design costs. With standards expressed electronically and using a knowledge-based approach, a rule-based system for the automatic design of standardized structural details is presented. For selected problems the corresponding rule formulations are developed; more advanced design tasks are solved by a bottom-up approach. As a result, the automatic, standards compliant design and validation is achieved, hence ensuring consistency as well as reducing the probability of design errors

Computational intelligence for measuring macro-knowledge competitiveness

The aim of this research is to investigate the utilisation of Computational Intelligence methods for constructing Synthetic Composite Indicators (SCI). In particular for delivering a Unified Macro-Knowledge Competitiveness Indicator (UKCI) to enable consistent and transparent assessments and forecasting of the progress and competitiveness of Knowledge Based Economy (KBE). SCI are assessment tools usually constructed to evaluate and contrast entities performance by aggregating intangible measures in many areas such as economy, education, technology and innovation. SCI key value is inhibited in its capacity to aggregate complex and multi-dimensional variables into a single meaningful value. As a result, SCIs have been considered as one of the most important tools for macro-level and strategic decision making. Considering the shortcomings of the existing SCI, this study is proposing an alternative approach to develop Intelligent Synthetic Composite Indicators (iSCI). The suggested approach utilizes Fuzzy Proximity Knowledge Mining technique to build the qualitative taxonomy initially, and Fuzzy c-mean is employed to form the new composite indicators