Taxonomy Development

Taxonomy is a systematic representation of a system s existence (McKelvey 1982). Accordingly, taxonomy is built based on principles of system theory. It is a mechanism for structuring the knowledge about a certain system domain. The process of taxonomy development consists of information collection, systematic analysis, and classification of system attributes. 

Problem taxonomy provides the overall framework under which problem-oriented information system components can be designed and implemented. 

Supply chain problem taxonomy comprises (a) classification of supply chain problems, (b) classification of problem solving methodologies for supply chain 

The most downstream supply chain unit observes an external demand, transmitted up on a supply chain as inventory replenishment orders move from one unit to another. It has been observed that substantial information distortion may occur during this transmission. This information distortion, known as the bullwhip effect, appears as an order variance increase as one moves up the supply chain. 

Different problem models have the same representation format and characteristics vocabulary, thus providing standardization of information representation in the supply chain domain. Problem model taxonomy serves as a meta-model for knowledge model generation and ontology engineering. Ontology inherits concepts, subsumption relationships, and characteristics from the problem model, thus 

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The CCPS Taxonomy developed for this book is one step toward accumulating and collating equipment reliability data for the CPI. Ideally, it will be expanded and modified as more companies make chemical process equipment failure rates and reliability data available. We expect that CCPS will update this book and the CCPS generic data base as new information becomes available. The taxonomy may also require modification where experience shows it is needed. We would appreciate any contribution from readers to these ends. 

Follette, W. C., St Houts, A. C. (1996). Models of scientific progress and the role of theory in taxonomy development A case study of the DSM. Journal of Consulting and Clinical Psychology, 64, 1120-1132. 

An independent validation of this mapping is the universal educational taxonomy developed by UNESCO [9]. They have proposed that all education should be organized around four fundamental types of learning ... 

Binomial nomenclature The system of taxonomy developed by Linnaeus in which each organism is assigned a genus and specific epithet. 

Chapter 3—CCPS Taxonomy Explains the CCPS taxonomy. Discusses the rationale and process for its development and the factors considered in its construction. 

To properly use failure rate data, the engineer or risk analyst must have an understanding of failure rates, their origin and limitations. This chapter discusses the types and source of failure rate data, the failure model used in computations, the confidence, tolerance and uncertainties in the development of failure rates and taxonomies which can store the data and influence their derivation. 

This chapter reviews the structure, rationale, and method used for the development of the CCPS Taxonomy and explains how to use it. Key elements of the CCPS Taxonomy that are explained include equipment, service, and failure description. The CCPS Taxonomy is listed in Appendix A. 

The development of the CCPS Taxonomy was essential, and it is one of the most useful results of preparing this book. The first step in creating the taxonomy was to develop a list of equipment to be included. This was accomplished by reviewing the equipment lists of over 300 different chemical processes summarized by SRI International in their Process Economics series. These lists were used in conjunction with the CCPS Equipment Re-... 

Many of the data cells defined by the CCPS Taxonomy are not presented in Chapter 5 because no appropriate data were available. It is hoped that this book will promote the development of new data by the CPI to fill these empty cells. As new data are collected, modifications to the CCPS Taxonomy may be required to better reflect reliability influences. The new data should provide better answers to the following questions ... 

The development of the CCPS Taxonomy provides an enormous number of data cells, each with its unique taxonomy number. To conserve space, the CCPS Taxonomy has been condensed for presentation in Appendix A. Figure 3.3 is an example page from Appendix A. 

Section 5.5 presents a data sheet for each cell in the taxonomy that contains failure rate data. Empty data cells are not presented. Filled data cells are listed by their CCPS Taxonomy number in Table 5.2 as an aid to the user. The CCPS data sheet format was developed from a number of sources including OREDA and IEEE Std. 500-1984. The format is presented in Figure 5.3, and its data elements are explained below ... 

Ideally, maintenance records should be organized by a classification method compatible with the CCPS Taxonomy in Appendix A and the equipment boundaries in Section 5.5, Generic Failure Rate Data Base. It is important to remember that the taxonomy presented was developed to group equipment into classes that are differentiated by their reliability rather than their design characteristics. Records maintained in this fashion allow the analyst to more easily determine the total pieces of equipment and number failures. 

Once it is determined that data exist, the next step is to begin the collection process. If sufficient thought and training is provided in the development and operation of the maintenance and operating reporting systems, much of the collection process can be automated. Automation assumes that a well-thought-out taxonomy is in place. If this is not the case, then an analyst must collect and review the records manually. In either case, the analyst must collect data from the plant sources previously discussed in order to determine the numerator (number of failures within a unique plant equipment population), and denominator (the operating time or number of demands for the equipment) of the equation to calculate failure rates. 

Shwartz, Y, Ben-Zvi, R., Hofstein, A. (2006). The use of scientific literacy taxonomy for assessing the development of chemieal literacy among high-school students. Chemical Education Research and Practice, 7(4), 203-225. 

A taxonomic note there have been substantial developments in the taxonomy of pseudomonads, and many new genera have been proposed including, for example, Sphingomonas, Comamonas, and Variovorax, while denitrifying organisms described as pseudomonads have been referred to the general Thauera and Azoarcus (Anders et al. 1995). 

Marlatt GA (1996). Taxonomy of high-risk situations for alcohol relapse Evolution and development of a cognitive-behavioral model. Addiction, 91, S37-49. 

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