Fault finding and failure predicting techniques in manufacturing and production systems often involve forecasting failures, their effects, and occurrences. The majority of these techniques predict failures that may appear during the regular system production time. However, they do not estimate the failure modes and they require extensive source code instrumentation. In this study, we suggest an approach for predicting failure occurrences and modes during system production time intervals at the University of Hail (UoH). The aim of this project is to implement failure mode effect and criticality analysis (FMECA) on computer integrated manufacturing (CIM) conveyors to determine the effect of various failures on the CIM conveyor belt by ranking and prioritizing each failure according to its risk priority number (RPN). We incorporated the results of FMECA in the development of formal specifications of fail-safe CIM conveyor belt systems. The results show that the highest RPN values are for motor over current failure (450), conveyor chase of vibration (400), belt run off at the head pulley (200), accumulated dirt (180), and Bowed belt (150). The study concludes that performing FMECA is highly effective in improving CIM conveyor belt reliability and safety in the mechanical engineering workshop at UoH.

Additive Manufacturing technologies are widely employed in the production of models for a range of industries. However, to-date little explicit research attention has examined the way in which the Laser Sintering technologies can be used in the specific application of architectural models. To evaluate the suitability of the process, this research develops a SWOT analysis of the Laser Sintering technologies for this application, highlighting not only the current advantages and disadvantages, but also future opportunities and threats which can be observed. From this assessment, the paper demonstrates the use of LS through the implementation of a four-stage model, supported by two examples of commercially produced architectural models.

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