Integrated Intelligent Equipment Health Management System to Support Life Cycle Decisions Considering Environmentally Conscious Production

Abstract

Integrated Intelligent Equipment Health Management System (IIEHMS) is a systematic engineering design Framework that includes multi-functional disciplines (such as mechanical, electrical, optical and software engineering, quality assurance, and manufacturing) with their partners and suppliers works together to achieve a green topology plant with respect to life cycle cost. The proposed structural framework is defined as fitness for operation at any time during plant life cycle. Plant life cycle includes the entire spectrum of activities; beginning with the identification of need and extending through plant design and development, production and/or construction, operational use and sustaining maintenance and support, and plant retirement and material disposal. The methodology recognizes five main aspects of the framework as follows: a) Plant Topology and Semantic Knowledge Acquisition Modeling, to synchronize different failure mechanisms database, environment and safety incident and accident reports, and properly retrieve recorded data and synchronize them during decision making process b) Equipment Failure Reasoning & Modeling, to better understand, represent and address equipment failure mode and their impacts on process, environment and human health c) Adaptive Intelligent Fault Diagnosis & Prognosis, which is fault diagnosis process modeling and recommendations including fault detection, fault isolation, scenario assessment and mitigation plan according to Environmental/safety/Health/Business requirements, d) Green Assessment of diagnosis scenarios, to particularly evaluate CO 2 emissions, the consequence of each failure scenario from the view point of pollution, risk, and global warming human health and ecological risks due to toxicity of pollutants emitted into the environment and social impact e) Reliability, Maintainability and Availability prediction and lifetime estimation and, to calculate some measure of performance that can be used in the instantaneous actions decision making, and to prevent future accidents through preventive actions f) Optimization of purchasing cost considering lifetime, warranty and environmental consciousness, to choose suppliers that minimize LCC and maximize the reliability of equipment and spare parts. Moreover, in the model, we incorporated failure mode, effects, and criticality analysis (FMECA) through which an enterprise is able to evaluate the external failure costs of purchased equipment/ components in order to optimize their choice of suppliers/vendors who provide better components for operation. Those aspects are included in an Equipment Health Management System that aims at assuring the best actions and decisions during plant life cycle and lifetime. They are linked to the result-type information and knowledge flows coming from internal/external parties, experts and stake holders and finally from the dynamic and continuous fault recognition process.