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|Introduction In the same way that a blueprint communicates informa¬tion about a structure, a systems architecture should provide information that guides the construction and implementation of a computing system. Taking the blueprint analogy a step further, a plot plan can also show where, in the "bigger picture," a particular design fits (if in fact it does) and what a builder needs to know about the environment in which he or she will operate. In the context of business systems, a meaningful architecture should convey the following: • the primary purpose of computer-based systems rela¬tive to particular tasks or operations, • the relationship of the systems to each other and an indication of their interaction and dependencies, • the relationship of the systems relative to the organiza¬tion and its objectives, • indications of where IS/IT resources can best be allo¬cated to support the organization and • the overall context in which new systems and technolo¬gies can be assessed for both their impacts on current systems and on the organization itself. In theory, a well-designed systems architecture should allow an organization to focus its resources on those aspects of its business that matter most, thus, leveraging investments in information technology to a competitive advantage. In addition, the way that a computing systems architecture is represented should be un¬derstandable to non-IT staff, and it should be eas¬ily recognized by the people it supports. This pa¬per attempts to show that a meaningful systems model exists and that its applica¬tion to mining can achieve the desired results. The following discus¬sion is based on the au¬thors interpretation of a concept referred to as the computer integrated manu¬acturing (CIM) model, as developed by Allen-Bradley. An inherent strength of the CIM approach is that the model combines aspects of business-reporting structures with the manufacturing process itself. What results is a systems frame¬work that is aligned with relevant business processes and is, therefore, easier for non-IS/IT personnel to interpret. The successful application of the CIM model can be seen in a large number of both discrete and process-manufacturing facilities throughout the United States. This paper provides a brief overview of the CIM model and then describes how the model can be applied at a conceptual level to the mining industry. Finally, this paper proposes an extension to the CIM model that the authors believe will make it easier to understand and apply. CIM model As shown on Fig. 1, the CIM model begins with the most detailed levels of process equipment and works its way up to the highest level of consolidated financial reporting. Systems at each level are characterized by common attributes, users, time frames, etc., providing a clear picture of their interac¬tion. Further analysis of the relationships between systems and between levels provides insight into the opportunities for integration. Regardless of the industry or processes involved, the CIM model provides a framework in which the characteristics of systems and the data they manage can be predicted based on the nature of the business function they support. In general, as data moves upward from the lower rungs of the CIM model, it changes from de¬scribing the physical na¬ture of a process to describ¬ing its financial aspects (e.g., from productivity to cost). The time frame to which data applies also transitions from a very short duration, perhaps only milliseconds, to financial or regulatory reporting time frames that may span years. In a simi¬|