A. Azzini, P. Ceravolo, A. Corallo, E. Damiani, M. Lazoi, Manuela Marra
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引用次数: 0
Abstract
The value of product lifecycle management systems (PLMS) is more and more recognised by companies and its use current has enormously increased. It is mainly used during the product design when different roles collaborate for sharing models, take review decisions, and approve or reject preliminary results. Often, companies have a general 'picture' about the processes involving PLMS (who performs an activity, when it is performed, what is done) but this knowledge can be reinforced, improved and modified using process mining. Here the knowledge is extracted from the event logs, and model-aware analytics are generated to evaluate the modelled, known and executed process. The business rules filter the logs and verify the impact on the process mining metrics to minimise the divergences between modelled and actual processes and improve the resulting quality metrics. The results help business users to identify lines of investigation for deviations from expected behaviour and propose improvement measures.
期刊介绍:
Product Lifecycle Management (PLM) is generally defined as a strategic business approach for the effective management and use of corporate intellectual capital. Today, challenges faced by product development teams include globalisation, outsourcing, mass customisation, fast innovation and product traceability. These challenges enhance the need for collaborating environments and knowledge management along the product lifecycle stages. PLM systems are gaining acceptance for managing all information about the corporation’s products throughout their full lifecycle, from conceptualisation to operations and disposal. The PLM philosophy and systems aim at providing support to an even broader range of engineering and business activities.