Cladogram

This article presents the findings of an investigation into the classification of manufacturing systems based on cladistics and the theory of natural selection. The article describes the benefits and application of cladistics classifications for those concerned with manufacturing advancement and technology management. The information presented provides researchers and consultants who have no prior knowledge of classification theory, with an introduction to this school of classification, along with rules and guidelines on how to construct, validate and analyse a manufacturing system cladogram.

This paper presents a new method for rapid simulation model generation using cladistics, a technique commonly used for evolutionary analysis in biology. In this research, cladistics is adopted as a basis for classification of problems typically found in manufacturing systems particularly assembly lines. The basic premise in this research is that manufacturing systems evolve (e.g. from craft production to mass production to lean production) and therefore their problems also evolve over time. Using cladistics, this evolution can be traced as the problems and their characteristics are hierarchically grouped in the form of phylogenetic tree or also known as cladogram. Model templates consisting of both physical and performance measures components were then developed from the cladogram. A prototype consisting of a secondary user interface was developed to link the template and the simulation engine. The prototype allows novice modellers to quickly build the model by first suggesting the most appropriate template to the problem being solved using simulation and then providing all the modelling constructs to facilitate model building. The innovative feature of the user interface lies in the functionalities which are capable of receiving and processing the data, identifying the most appropriate template and generating routing summary based on the users' requirements in real time.

Prior research has shown that reasoning with cladograms is a skill that must be taught. Novice students, who do not understand the peculiarities of the representational system, can rely only upon prior content knowledge and perceptual resources (e.g., embodied and culturally-learned spatial metaphors (Tversky, Kugelmass, & Winter, 1991) and Gestalt perception (Novick & Catley, 2007) to make sense of them. The problem is that students' prior knowledge is sometimes incorrect or incomplete. They rely upon misconceived folk theories of evolution as a linear transformation through successive stages; and their intuitive perceptions often counter the obscure symbolic rules by which the cladogram operates. It is such that even with instruction, many students tend to make errors when interpreting cladograms (Meir et al., 2007), which keeps them from mastering an important component evolutionary reasoning.

Abstract Prior research has shown that reasoning with cladograms is a skill that must be taught. Novice students, who do not understand the peculiarities of the representational system, can rely only upon prior content knowledge and perceptual resources (eg, embodied and culturally-learned spatial metaphors (Tversky, Kugelmass, & Winter, 1991) and Gestalt perception (Novick & Catley, 2007) to make sense of them. The problem is that students' prior knowledge is sometimes incorrect or incomplete. They rely upon ...

This article presents a case for the construction of a formal classification of manufacturing systems using cladistics, a technique from the biological school of classification. A seven-stage framework for producing a manufacturing cladogram is presented, along with a pilot case study example. This article describes the role that classification plays in the pure and applied sciences, and the social sciences and reviews the status of existing manufacturing classifications. If organisational diversity and organisational change processes are governed by evolutionary mechanisms, studies of organisations based on an evolutionary approach such as cladistics could have potential, because as March states “there is natural speculation that organisations, like species can be engineered by understanding the evolutionary processes well enough to intervene and produce competitive organisational effects” [March JG. The evolution of evolution. In: Baum JAC, Singh JV, editors. Evolutionary dynamics of organizations. Oxford University Press, 1994. p. 39-52]. It is suggested that a cladistic study could provide organisations with a “knowledge map” of the ecosystem in which they exist and by using this phylogenetic and situational analysis, they could determine coherent and appropriate action for the specification of change.