Methodologies for Practical Applications of Linnaean and Cladistic Classification of Production Systems

The aim of this PhD thesis was to present an attempt to unify the various discrete manufacturing system classifications, typologies and taxonomies, and thus develop two related conceptual schemes: complementary hierarchical and ‘cladistic’ classifications. The classifications would form the basis for a further practical stage of the research – a web-based expert system and diagnostic tool that would complement a larger software system architecture within the European Commission Framework 7 Programme funded Copernico project. The aim of Copernico was to simplify, and make accessible, essential tools for the rapid design, simulation and virtual prototyping of factories, based on the classifications developed as part of this PhD. The classifications also have a novel use in an educational context as they simplify and organise extant knowledge and adds another layer of information in terms of the evolutionary relationships between manufacturing systems. There were two main stages for the research methods, with eight re-iterative steps, for constructing cladistic and hierarchical classifications: one for theory building, using secondary and observational data, producing the conceptual ‘cladogram’; the other for theory testing in order to develop theory further, using quantitative data, producing the final factual cladogram. After defining the classification problem and identifying the range of ‘Species’ to include, the evolutionary-unique, product, process and system characteristics of each Species were determined, systematically coded, and subjected to polarity ascertainment. This in turn led to the conceptual cladogram. A complementary classification organised this information hierarchically and grouped Species under ‘Genera’, ‘Families’, ‘Orders’ and ‘Class’ based on evolutionary proximity. Using the cladistic approach, the evolutionary relationships between fifty-three candidate Species of manufacturing systems, using ‘descriptors’ drawn from a library of twelve characters with a total of eighty-four states, were hypothesised, described and presented diagrammatically as a conceptual cladogram. The manufacturing Species were then organised in a hierarchical conceptual classification with fourteen Genera, six Families and three Orders under one Class of Discrete Manufacturing. The results presented up to this point in the thesis are largely conceptual in nature and based on secondary data including the Operations and Production Management literature, company records, annual reports, business plans and technical data (layout plans, control/scheduling strategies, etc). The classifications are, however, arguably and demonstrably consistent with, and synthesise many of the established typologies in the Operations and Production Management and other literature. To further address the limitation of this conceptual work, the next major stage of research, the testing and further development of theory, which produces the final factual cladogram, was grounded in quantitative data from a representative sample of discrete manufacturers using an observation-assisted survey instrument. A benchmarking tool, by which manufacturing organisations can easily locate where they are in evolutionary history, identify where they want to be and how to get there, was been produced. The utilisation of this tool is characterised by a speed-read technique using the Linnaean hierarchy of Discrete Manufacturing Species as a map where the manufacturer can search out its closest present identity organisation. The diagnostic tool used to explore the fitness of an individual firm’s layout Species is a Kiveat diagram of ‘spider-gram’. This gives a visualising representation of the comparison between the problem Specimen of the Species and the ‘ideal’ or ‘textbook’ Species. A critical review of previous manufacturing cladistics research, revealed that although the steps to construct a cladistic classification were thoroughly outlined, the only applications were industry specific. Therefore the work presented here was the first attempt at unifying extant classifications producing complementary, comprehensive classifications of generic production systems that span industrial sectors of discrete manufacturing. The uniqueness of the work presented, however, was, within the framework above, to apply a speed-read technique and a spider-gram comparison as tools for improving the fitness/performance of a manufacturing organisation.