A Maturity Assessment Procedure Model for Realizing Knowledge-Based Maintenance Strategies in Smart Manufacturing Enterprises
The digital transformation of manufacturing industries currently re-invents conventional production paradigms through the creation of cyber-physical production systems (CPPS) and smart manufacturing networks. Novel knowledge-based maintenance (KBM) strategies and models are regarded as a key enabler in order to manage the increasing complexity and automatization of CPPS. Thus, securing and improving machine availability and process stability are accomplished. Although industrial decision makers are willing to invest in renovating and enhancing their companies' maintenance strategy, they lack knowledge regarding their readiness levels in realizing and deploying KBM. In particular, they doubt whether their companies hold fundamental competence and capacity (i.e. appropriate methods for data analytics and systematic guidance) towards realizing KBM. In this paper, the authors present a holistic procedure model that assesses a company´s individual status quo in KBM and enables the identification of strengths and weaknesses on operative, tactical and strategic level following a multidimensional analytical approach. The model thereby builds on the assessment of more than 35 quality indicators assigned to a maintenance execution and data management dimension. The indicators feed into a mathematical calculation of data, information, knowledge and maintenance quality factors. The authors present the model's development and content. Applying the model to an Austrian manufacturing company, its KBM readiness and maturity level for the creation of a predictive maintenance strategy under the premise of supporting prompt and efficient decision making is assessed. Feedback and validation of the results reveals both scientifically valuable, systematic and transparent applicability in real production environments.