Abdul Samad Kazi

Knowledge creation and management: the case of fortum engineering ltd

A clear understanding of what constitutes knowledge, knowledge management, knowledge processes (identification, collection, organisation, sharing, adaptation, usage and re-creation), and knowledge enablers (culture, technology, measurement, strategy and leadership) is essential. The aim is both to increase and to enable an individual to participate in decision making based on value-added information in addition to being in a position to exercise control over his or her work domain. This chapter advocates the appropriate use of technology for culture and social norms, which may be seen as a core need for knowledge management success. The coverage is primarily on knowledge know-how and, more so perhaps, minimal critical specification in terms of sociotechnical principles (Cherns, 1976, 1987).

Functional Requirements for Inter-enterprise Intranet Services

A core requirement for inter-enterprise collaboration in a virtual enterprise (VE) is the availability of an inter-enterprise Intranet service that facilitates the seamless flow of data and information between the different actors involved in addition to fostering an environment for collaboration. This paper is based on explorations and findings of trying to find/develop an inter-enterprise Intranet service for the participants of a virtual enterprise. Some required functionalities/support that were identified include: concurrent engineering, suitability to project business conditions, open system architecture, electronic document management, product structure/configuration management, access control, redlining/mark-up, groupwork support, user profiling, version and revision management, workflow management, distributed databases, application integration, and application launching. The paper concludes by illustrating an envisioned system architecture for inter-enterprise intranet services.

Model-based collaborative virtual engineering in textile machinery industry: Living lab case study

Client demand for on-of-a-kind products and services is leading to a paradigm shift in the way organisations, and especially SMEs collaborate to design, customise, configure, and manage specialised products and services. This paper presents the findings from a living lab case study of a textile machinery manufacturing SME that uses the concept of model-based collaborative virtual engineering and supporting tools in the form of a mashed-up model-server environment to support the needs of its mobile engineers. Initial findings reveal that use of such an environment provides real-time (on the finger-tips) access to relevant data through a single interface, reduces rework, provides real-time updates, supports on-the-move interactive collaboration, decreases meeting times, and allows for better response to and satisfaction of client needs.

Good practice capture using social processes: Experiences of YIT Construction Ltd.

The construction industry is a project based one with each project being the production or provision of a one-of-a-kind product or service. Each day on a typical construction site brings forth a new problem for which where possible, a new solution is devised on the site. This is rarely, if at all documented. In simple terms, valuable knowledge and experience gained is lost. What remains is stored in the minds of those who were a part of the problem and the solution. The most appropriate means of capturing this knowledge has been identified to be through a set of well defined “social processes” such as action evaluations, internal interest groups, etc. A set of critical “intervention points” were identified where these social processes would be triggered. Recent experience from YIT Construction Ltd. reveals that social processes form an effective means for the capture of experience and knowledge in project based businesses such as construction.

Modelling for Designing, Managing and Improving Virtual Enterprises in One-of-a-kind Business

The paper starts with an exploration of the current conceptual underpinnings,paradigms and theories of production from the point of view of modelling. It is argued that modelling should bear on designing, controlling and improving production systems. Modelling should orient towards the existing three conceptual views on production: transformation, flow and value generation. Furthermore, modelling should cover both the physical process and the control information process. Finally, modelling should respond to the specific needs of virtual production in one-of-a-kind business, for example, the design of the production system accentuates. Two sets of modelling tools are analyzed against this framework: comprehensive modelling approaches and specific, more partial tools for virtual production. These results suggest that, at the level of research, the search for a unified conceptualization of production should be emphasized; only based on such a foundation can truly comprehensive and integrated modelling tools be constructed. At the more practical level, modelling efforts - in lack of tools based on a unified conceptualization - have to be partial; however, these efforts should be structured so that various modelling approaches could more easily be interfaced with each other, and the limitations of the particular tools in use should be clearly recognized.

Knowledge Creation at FORTUM Engineering

The creation and management of knowledge is considered a key enabler of value added business process delivery. This paper presents the findings of the main efforts towards knowledge creation at Fortum Engineering (FE), an engineering, procurement, and construction provider of power plants. Dealing with different levels of knowledge, it is necessary for FE to provide an environment that is able to translate and codify its tacit knowledge into explicit knowledge to support the definition of power plant configurations using expert applications. Where data or information is not available in a tangible form for translation, some mapping methodologies may be used to render the tacit knowledge meaningful and usable. FEs suggested, knowledge creation and management environment involves; mining of data structures to capture and transfer information into the appropriate knowledge level, manual and automated inputs and rule definitions to capture and manage knowledge on different knowledge levels, and the correlation of knowledge and its data or information source using mind mapping tools. The focus of this paper is to first justify the need for knowledge creation at FE and then to illustrate the envisioned knowledge creation environment. Key phases of the knowledge creation process are furthermore explained.