• Energy Research

Today, to properly address circular economy practices, strategic decisions encompassing all the various life cycle stages of products or services have become critically important in the market. However, companies still have difficulties in balancing the technical and environmental requirements of their offerings, and numerous studies outline the need for more research on ecodesign tools to support them in decision-making. To reduce such a research gap, a decision-making framework based on the integrated use of the quality function deployment for the environment (QFDE), analytic hierarchy process (AHP), strengths, weaknesses, opportunities, and threats (SWOT), and TOWS matrix methods was developed through a case study related to the provision of photovoltaic solar systems for domestic use. The results achieved show that to better enhance the company’s offering of ensuring customer satisfaction and green compliance, a shift towards a product–service system (PSS) approach is required, and practical implementation strategies are suggested. Overall, this study contributes to the environmental research literature by streamlining marketing strategy planning decision-making through a novel QFD-based approach that aligns customer requirements with environmental concerns and improvement options. Thus, it provides both academics and practitioners with a useful framework to better address the implementation of circular economy practices.

The optimization of a product’s whole life cycle has become a mandatory task for manufacturers seeking to deal with circular economy requirements while gaining competitiveness in the market. In order to achieve such a sustainability goal, alignment of production, distribution, and field service activities is needed. In the literature, numerous studies indicate the product–service system (PSS) approach as one of the most promising business models to combine the needs of manufacturers and customers in an efficient and effective manner. However, PSS solutions aimed at practically optimizing supply chain management have scarcely been addressed. In order to reduce this gap, the current study proposes a procedure based on the PSS Functional Matrix, the Screening Life Cycle Modelling (SLCM) method, and stock management theory to optimize aftermarket services based on market demand. A case study in the medical equipment sector, where market demand can fluctuate during the contract period, is presented. The analytical results show beneficial effects in terms of both costs and environmental impact, suggesting the need for further research to augment knowledge on PSS and supply chain management. In particular, the PSS allowed the company to customize the manufacturer’s business model, adapting the supply of aftermarket services to varying customer needs.

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.

Optimal spare parts management strategies allow sustaining a system’s availability, while ensuring timely and effective maintenance. Following a systemic perspective, this paper starts from the Multi-Echelon Technique for Recoverable Item Control (METRIC) to investigate the potential use of a Weibull distribution for modelling items’ demand in case of failure. Adapting the analytic formulation of METRIC through a Discrete Weibull distribution, this study originally proposes a METRIC-based model (DW-METRIC) to be used for modelling the stochastic demand in multi-item systems, in order to ensure process sustainability. The DW-METRIC has been tested in a case study related to an industrial plant constituted by 98 items in a passive redundancy configuration. Comparing the results via a simulation model, the outcomes of the study allow defining applicability criteria for the DW-METRIC, in those settings where the DW-METRIC offers more accurate estimations than the traditional METRIC.