Monitoring provides a valid support to detect problems, prevent undesired situations, avoid repeating mistakes, as well as identifying virtuous behaviors both in daily production activities and innovation-oriented initiatives. Key performance indicators (KPIs) are metrics that provide quantifiable data to assess how organizations, business units or individuals are performing against predefined goals and target. This chapter presents some relevant works in data integration and performance measurement. The architecture of the solution is then introduced, which is followed by a discussion on semantic-based tools and services. The BIVEE project relies on a knowledge-centric approach in which the semantic layer, namely the production and innovation knowledge repository (PIKR). To support end-users in the management of KPI reference ontology (KPIOnto) and the extraction of KPI data for performance monitoring and comparison, two web applications named KPIOnto Editor and KPIExplorer are developed and describes in the chapter.
Monitoring Innovation and Production Improvement / Diamantini, Claudia; Potena, Domenico; Storti, Emanuele. - STAMPA. - (2015), pp. 189-212. [10.1002/9781119145622.ch11]
Monitoring Innovation and Production Improvement
DIAMANTINI, Claudia;POTENA, Domenico;STORTI, EMANUELE
2015-01-01
Abstract
Monitoring provides a valid support to detect problems, prevent undesired situations, avoid repeating mistakes, as well as identifying virtuous behaviors both in daily production activities and innovation-oriented initiatives. Key performance indicators (KPIs) are metrics that provide quantifiable data to assess how organizations, business units or individuals are performing against predefined goals and target. This chapter presents some relevant works in data integration and performance measurement. The architecture of the solution is then introduced, which is followed by a discussion on semantic-based tools and services. The BIVEE project relies on a knowledge-centric approach in which the semantic layer, namely the production and innovation knowledge repository (PIKR). To support end-users in the management of KPI reference ontology (KPIOnto) and the extraction of KPI data for performance monitoring and comparison, two web applications named KPIOnto Editor and KPIExplorer are developed and describes in the chapter.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.