In recent years there has been appreciable academic activity in manufacturing value creation resulting in that the ability to create value is based on the competence to make decisions and implement strategies; even though this evidence it is still difficult to understand where the company's weak points are located so value modeling approaching is arising. In this study Authors first report a qualitative review on value creation and modeling based on the identification, selection and analysis of about 100 papers, then specify the value concept within manufacturing companies. Within this context the Authors describe a novel methodology for manufacturing value modeling from strategic level down to operational improvements. The methodology and the related mapping and analysis tools have been co-developed with Siemens MES division within Industry 4.0 context. The Manufacturing Value Modeling Methodology (MVMM) is based on 5 steps: Value Map, Maturity Model, Gap and Process Analysis, Validation and Improvement Areas Definition. Through this methodological approach, a series of structured interviews allowing to construct the value map accordingly to the current company maturity model and the relationships between the strategic objectives and operational practices, capabilities, and methods. Combining the assessments interview with the Company' resources, infrastructure and IT structures, it is possible to establish a current level of the company. The mapping step is followed by a gap and process analysis, assessing most relevant areas for the creation of value aiming at constructing an interventions roadmap, setting out priorities and activities to be improved. The selection of the improvement areas defines process initiatives, KPIs and interventions to improve business alignment. To provide a practical view of the methodology a sample of the Value Modeler tool is presented and discussed.

A Novel Methodology for Manufacturing Firms Value Modeling and Mapping to Improve Operational Performance in the Industry 4.0 Era

TONELLI, FLAVIO;DEMARTINI, MELISSA;
2016-01-01

Abstract

In recent years there has been appreciable academic activity in manufacturing value creation resulting in that the ability to create value is based on the competence to make decisions and implement strategies; even though this evidence it is still difficult to understand where the company's weak points are located so value modeling approaching is arising. In this study Authors first report a qualitative review on value creation and modeling based on the identification, selection and analysis of about 100 papers, then specify the value concept within manufacturing companies. Within this context the Authors describe a novel methodology for manufacturing value modeling from strategic level down to operational improvements. The methodology and the related mapping and analysis tools have been co-developed with Siemens MES division within Industry 4.0 context. The Manufacturing Value Modeling Methodology (MVMM) is based on 5 steps: Value Map, Maturity Model, Gap and Process Analysis, Validation and Improvement Areas Definition. Through this methodological approach, a series of structured interviews allowing to construct the value map accordingly to the current company maturity model and the relationships between the strategic objectives and operational practices, capabilities, and methods. Combining the assessments interview with the Company' resources, infrastructure and IT structures, it is possible to establish a current level of the company. The mapping step is followed by a gap and process analysis, assessing most relevant areas for the creation of value aiming at constructing an interventions roadmap, setting out priorities and activities to be improved. The selection of the improvement areas defines process initiatives, KPIs and interventions to improve business alignment. To provide a practical view of the methodology a sample of the Value Modeler tool is presented and discussed.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/876080
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