M Sinclair

A method for decision support for the allocation of functions and the design of jobs in manufacturing, based on knowledge requirements

We discuss an approach based on the configuration of knowledge required to carry out manufacturing functions. It is intended to address the design of new business processes, rather than upgrades of cells, or similar entities. The basic premise is that an organisation can be construed as a configuration of knowledge, embodied in humans and machines, which utilises data to create information (e.g. the product data model), and its physical manifestation (products for sale). The problem is to optimise this configuration of knowledge and its allocation to humans and machines. The starting points for this are: The internal and external operating environment of the manufacturing process; a knowledge taxonomy for manufacturing; and a function-based description of the activities in the process. We outline a methodology, developed in research and consultancy projects, which acts as a decision support tool in the allocation of functions, the definition of human roles, and the distribution of management functions to ...

Models and Metaphors: Complexity Theory and Through-Life Management in the Built Environment

Abstract Complexity thinking may have both modelling and metaphorical applications in the through-life management of the built environment. These two distinct approaches are examined and compared. In the first instance, some of the sources of complexity in the design, construction and maintenance of the built environment are identified. The metaphorical use of complexity in management thinking and its application in the built environment are briefly examined. This is followed by an exploration of modelling techniques relevant to built environment concerns. Non-linear and complex mathematical techniques such as fuzzy logic, cellular automata and attractors, may be applicable to their analysis. Existing software tools are identified and examples of successful built environment applications of complexity modelling are given. Some issues that arise include the definition of phenomena in a mathematically usable way, the functionality of available software and the possibility of going beyond representational modelling. Further questions arising from the application of complexity thinking are discussed, including the possibilities for confusion that arise from the use of metaphor. The metaphor of a ‘commentary machine’ is suggested as a possible way forward and it is suggested that an appropriate linguistic analysis can in certain situations reduce perceived complexity.