Search results

This paper presents a new and well-structured framework that aims to assess the current environmental impact from a Greenhouse Gas (GHG) emissions perspective. This tool includes a new set of Lean Key Performance Indicators (KPIs), which translates the well-known logic of Overall Equipment Effectiveness in the field of GHG emissions, that can progressively detect industrial losses that cause GHG emissions and support decision-making for implementing improvements.

The new metrics are presented with reference to two different perspectives: (1) to highlight the deviation of the current value of emissions from the target; (2) to adopt a diagnostic orientation not only to provide an assessment of current performance but also to search for the main causes of inefficiencies and to direct improvement implementations.

The proposed framework was applied to a major company operating in the plywood production sector. It identified emission-related losses at each stage of the production process, providing an overall performance evaluation of 53.1%. The industrial application shows how the indicators work in practice, and the framework as a whole, to assess GHG emissions related to industrial losses and to proper address improvement actions.

This paper scrutinizes a new set of Lean KPIs to assess the industrial losses causing GHG emissions and identifies some significant drawbacks. Then it proposes a new structure of losses and KPIs that not only quantify efficiency but also allow to identify viable countermeasures.

This paper presents Quick Changeover Design (QCD), which is a structured methodological approach for Original Equipment Manufacturers to drive and support the design of machines in terms of rapid changeover capability.

To improve the performance in terms of set up time, QCD addresses machine design from a single-minute digit exchange of die (SMED). Although conceived to aid the design of completely new machines, QCD can be adapted to support for simple design upgrades on pre-existing machines. The QCD is structured in three consecutive steps, each supported by specific tools and analysis forms to facilitate and better structure the designers' activities.

QCD helps equipment manufacturers to understand the current and future needs of the manufacturers' customers to: (1) anticipate the requirements for new and different set-up process; (2) prioritize the possible technical solutions; (3) build machines and equipment that are easy and fast to set-up under variable contexts. When applied to a production system consisting of machines subject to frequent or time-consuming set-up processes, QCD enhances both responsiveness to external market demands and internal control of factory operations.

The QCD approach is a support system for the development of completely new machines and is also particularly effective in upgrading existing ones. QCD's practical application is demonstrated using a case study concerning a vertical spindle machine.

The paper aims to contributes on the debates about University Idea Incubation by investigating the role and the engagement of different University's stakeholders in the process of opportunity recognition in an entrepreneurship education program targeted at students with an interdisciplinary background.

Through a longitudinal case study methodology, the Contamination Lab at University of Salento (Lecce, Italy), the learning approaches and the knowledge process to create an entrepreneurial awareness, mindset and capability in students with different educational background are presented.

The findings demonstrates the crucial role of stakeholders' engagement for business idea presentation, open innovation challenge, contamination workshop on specialized topics, enterprise projects are important vehicle for effective students' business ideas and innovative projects development in a multidisciplinary environment. The close interaction among students, academia, companies and institutions creates a favourable environment that enables opportunity identification, idea generation through a deep contamination of knowledge, skills and experiences.

Limitations include the need to generalise the results even if this limitation is typical of the case study methodology. Other research is necessary for an in-depth analysis in deep of the other Contamination Lab in Italy and to derive the “invariance traits” of this environment according to the features of the local entrepreneurial ecosystems.

Implications for practices include recommendations for designing innovative programs where the interactions between University-Institutions-Industry are realized.

A conceptual framework is proposed by defining all the entrepreneurial knowledge process and knowledge creation within the Contamination Lab, highlighting the contribution of the stakeholders in each phase and learning initiative of the program.