Managing knowledge within the manufacturing enterprise: an overview <s> Papers addressing different life cycle stages <s> Abstract Starting from the identification of the increased need for enterprise integration and real-time and up-to-date information, the paper briefly describes the CIMOSA concept, the enterprise modelling solution for identification of available information and its use in the operational processes of the manufacturing enterprise. CIMOSA has been developed by the ESPRIT Consortium AMICE and has been validated together with the ESPRIT projects CIMPRES, CODE and VOICE in multiple case studies and pilot implementations. Validation results have been used to improve the technical specifications of CIMOSA. Exploitation of CIMOSA has been started in the area of enterprise modelling, modelling tool developments and further enhancement of industrial pilot implementations of the Integrating Infrastructure. These efforts are being complemented by promotional activities aimed at increasing enterprise integration awareness and acceptance and support of standardisation activities on national, European and international level. Enterprise integration has not yet become the common industrial goal, nor the specific day-to-day operational tool in the manufacturing community that it should be. Lean enterprises, business re-engineering, concurrent engineering, management of change — identified as current management concerns — should be viewed as subsets of enterprise integration. The engineering of the enterprise has to be become an engineering discipline in its own right in order to solve the many problems in the operation of enterprises of the future. <s> BIB001 </s> Managing knowledge within the manufacturing enterprise: an overview <s> Papers addressing different life cycle stages <s> Enterprises are rather complex systems which have to be managed for their internal affairs, but more importantly for the many relations to the different environments in which they are operating. Today, these environments are changing much more rapidly and the need for relevant information becomes of paramount importance in the decision making processes at all levels of enterprise management. Fluctuations in market demands, technology evolution and changing regulations require very flexible enterprise operations, capable of reacting to those changes. These reactions must be based on relevant and up-to-date information which must be supported by new decision support technology. The challenges in decision support concern the identification of relevant information, easy access and intelligent use of this information. Building and maintaining the enterprise knowledge base and enabling its efficient use for decision support are major tasks of enterprise engineering. Enterprise integration and its subsequent operation in the global environment of customers, suppliers and regulatory bodies will heavily depend on the availability and the continuous extension of this knowledge base. Enterprise modelling will play an important role in creating the knowledge base and in using it for enterprise integration and operational decision support. The paper discusses enterprise engineering as an enterprise life-cycle oriented discipline for identification, design, and implementation of enterprises and their continuous evolution. Current problems in the field are identified and initiatives are presented. <s> BIB002 </s> Managing knowledge within the manufacturing enterprise: an overview <s> Papers addressing different life cycle stages <s> Abstract Technical services such as maintenance, retrofitting, refurbishing or user training can significantly influence the economic and ecologic performance of high quality investment goods, thus providing new and advanced user benefits. In order to systematically exploit these potentials the interrelations between physical products and non-physical services need to be considered proactively, resulting in the necessity for integrating corresponding product and service design processes. For this reason, a process for the systematic design of product related technical services is introduced that upon its modularization represents a promising starting point for linkage with corresponding product design processes. Life cycle oriented design of technical Product-Service Systems is thus supported. The presented concept is finally illustrated by means of an example from the investment goods industry. <s> BIB003
Product development is often described in a systematic sense, in which a sequence of activities, or design stages, is defined. A much cited example is developed by Ulrich and Eppinger  , consisting of a sequential model including planning, concept development, system level design, detail design, testing, and production. This view of the NPD process model does not describe the whole product life cycle, since it ends at 'production'. The move towards product life cycle models provides a more complete basis for information and data management, and from that perspective a more complete description of the information and knowledge required during the design stage. A manufacturer's view of a product's life cycle is described by Stark (Stark 2004) , in which five stages are proposed: imagine, define, realise, service, and retire. Stark's model adds the dimension of product support (service) and end of life, but it provides very little detail in the product definition stage. The life cycle model presented as part of the CIMOSA modelling framework shows the stages identification, concept, requirements, preliminary design, detailed design, implementation, operation and decommission BIB002 . This could be argued to be limited in the end of life section according to recent life cycle models "the product life cycle starts with product design, followed by product manufacturing, product servicing and product remanufacturing" BIB003 . The CIMOSA framework will be adopted since it includes multiple design phases and it includes stages in the life cycle beyond the 'use' phase. The CIMOSA modelling framework shown in Figure 4 has two additional dimensions: instantiation and view. Instantiation refers to the level at which the model is defined: "Generic enterprise modelling concepts provide means for modelling constructs consistency like language semantic and syntax's definitions through ontologies, formal languages, glossaries, etc. Partial enterprise models provide models which can be reused by modifying enterprise specific attributes of activities and processes… The elements identified in each life-cycle phase of the reference architecture are the building blocks or constructs to be used in the creation of a particular enterprise model." BIB002 Figure 4: CIMOSA modelling framework BIB002 View refers to a method for dividing the model: "This concept of views allows one to work with subsets of the model rather than with the complete model, providing especially the business user with reduced complexity for his particular area of concern. CIMOSA has defined four different modelling views (Function, Information, Resource and Organisation). However, this set of views may be extended if needed." BIB001 This analysis will show the intended life cycle phase for the proposed manufacturing knowledge methods and the granularity: whether it describes generic modelling concept or a partial enterprise model. Views are not appropriate in this analysis. The analysis shows total numbers according to columns (granularity). The numbers shown corresponding to life cycle stage refer to the number of methods and tools that contribute directly to that stage; those which are focused on supporting the particular needs of those activities. This removes the generic knowledge management or enterprise modelling methods that contribute to the whole product life cycle, and better reflects where the research focus is relevant to that particular stage of the product life cycle. The granularity addressed by the manufacturing knowledge research is very much biased towards the 'partial' (models which can be reused by modifying enterprise specific attributes): 62 of the 73 included in the analysis. There is still a clear focus on the generic: 11 of the 73 papers address fundamental research into modelling methods and knowledge and information structures. The life cycle stage analysis has shown that identification and concept tasks are not addressed in the manufacturing domain. To some extent this is a semantic mismatch; several papers would argue that they address conceptual design, however at this level the work is more closely matched to preliminary design. 3 papers addressed requirements methods -each one integrating requirements and preliminary design. 29 papers focused on preliminary design, 16 of which were also concerned with detail design aspects. 42 papers addressed detailed design, of which 9 related to generic, or fundamental, issues. 12 papers address implementation, or production. The manufacturing enterprise is described in Figure 3 , including the two sub-domains 'design' and 'production'. From that perspective it was shown that there is a design bias in the research. The life cycle analysis in Figure 5 also shows a design bias: a combined total of 47 papers contribute to the preliminary and detailed design phases. Production (implementation) has only 12. This indicates that the recent focus of the manufacturing knowledge domain is significantly biased towards design. The focus on design also indicates that researchers consider the manufacturing domain from an enterprise perspective. Of the remaining life cycle phases, operation (service) has only 1, and remanufacture / decommission has 0. Significant growth is expected in this area. The developing research area of product-service-systems (PSS) and a growing demand for end of life management will form a part of the future in this domain. Integration of PSS, design and manufacturing research is expected to follow as the domains mature.