In the literature, many applications of Digital Twin methodologies in the manufacturing, construction and oil and gas sectors have been proposed, but there is still no reference model specifically developed for risk control and prevention. In this context, this work develops a Digital Twin reference model in order to define conceptual guidelines to support the implementation of Digital Twin for risk prediction and prevention. The reference model proposed in this paper is made up of four main layers (Process industry physical space, Communication system, Digital Twin and User space), while the implementation steps of the reference model have been divided into five phases (Development of the risk assessment plan, Development of the communication and control system, Development of Digital Twin tools, Tools integration in a Digital Twin perspective and models and Platform validation). During the design and implementation phases of a Digital Twin, different criticalities must be taken into consideration concerning the need for deterministic transactions, a large number of pervasive devices, and standardization issues. Practical implications of the proposed reference model regard the possibility to detect, identify and develop corrective actions that can affect the safety of operators, the reduction of maintenance and operating costs, and more general improvements of the company business by intervening both in strictly technological and organizational terms.

Although many firms report large benefits from lean implementation, a lot of scepticism still remains regarding attainable results and the possibility to apply Lean approach outside high-volume manufacturing and stable context. In this work, combining field interviews with literature review, theoretical connections have been developed among Lean manufacturing techniques, operational responsiveness and company growth performances. A conceptual model has been proposed for investigating the network of influences among lean practices (supplier management, human resource management, just-in-time and total quality management practices), operational responsiveness (Product mix variety, Product innovation and Time effectiveness) and company growth performances in Italian companies. Using structural equation modelling, a second-order confirmatory factor analysis has been used to test the hypothesised relationships in the structural models. This study highlights that the operational responsiveness is only partially connected to a Lean strategy of a company. Indeed, the lean practices implementations are negatively influenced by product mix variety and innovation, while positively influenced by time effectiveness variables. Moreover, product mix variety and time effectiveness are the main characteristics of the operational responsiveness that positively influences company growth performances. So time effectiveness could be considered as a mediator between Lean best practices and firm growth. Moreover, no direct relationship has been found between lean bundles and firm’s performances. Lack of resources and mainly poor communication and managers’ commitment and support seem to be the main obstacles of lean implementation and success.