Schumacher, A., Erol, S., & Sihn, W. (2016). A maturity model for assessing Industry 4.0 readiness and maturity of manufacturing enterprises. In A. Nassehi & S. Newman (Eds.), The Sixth International Conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV2016) (pp. 161–166). Elsevier BV. https://doi.org/10.1016/j.procir.2016.07.040
The Sixth International Conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV2016)
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Volume:
52
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Date (published):
2016
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Event name:
The 6th International Conference on Changeable, Agile, Reconfigurable and Virtual Production
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Event date:
4-Sep-2016 - 6-Sep-2016
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Event place:
Bath England, EU
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Number of Pages:
6
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Publisher:
Elsevier BV
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Keywords:
General Materials Science; Industry 4.0; Maturity Model; Change Management; Strategic Management
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Abstract:
Manufacturing enterprises are currently facing substantial challenges with regard to disruptive concepts such as the Internet of Things, Cyber Physical Systems or Cloud-based Manufacturing - also referred to as Industry 4.0. Subsequently, increasing complexity on all firm levels creates uncertainty about respective organizational and technological capabilities and adequate strategies to develop them. In this paper we propose an empirically grounded novel model and its implementation to assess the Industry 4.0 maturity of industrial enterprises in the domain of discrete manufacturing. Our main goal was to extend the dominating technology focus of recently developed models by including organizational aspects. Overall we defined 9 dimensions and assigned 62 items to them for assessing Industry 4.0 maturity. The dimensions "Products", "Customers", "Operations" and "Technology" have been created to assess the basic enablers. Additionally, the dimensions "Strategy", "Leadership", Governance, "Culture" and "People" allow for including organizational aspects into the assessment. Afterwards, the model has been transformed into a practical tool and tested in several companies whereby one case is presented in the paper. First validations of the model's structure and content show that the model is transparent and easy to use and proved its applicability in real production environments.
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Research Areas:
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