Industry 4.0 makes a factory smart by applying advanced information systems and future-oriented technologies. Today, thanks to the application of the most innovative digital technologies offered by the new Industry 4.0 paradigm, in this Fourth Industrial Revolution, there is a significant "evolution" of many methodologies of Continuous Improvement, such as, e.g., Lean Six Sigma (LSS). Most of the tools of Lean Six Sigma relies on data to know in depth problems: data is necessary to drive any process improvement. The key issue is based on data integrity and on real time data. The aim of this paper consists of proving the efficiency of the so called "Lean Six Sigma 4.0". This paper deals with engineering approaches, here applied in HealthCare environment, in order to optimise the services supply process and to reduce the waste of resources (human and/or material), while improving the Quality of Experience (QoE) of the patients. Indeed, it has been proved that the huge growth in the HealthCare costs is due to inefficient use of available resources and not-optimised service processes. Applying Lean Six Sigma 4.0 it is possible to reduce HealthCare costs, improving at the same time the QoE perceived by the patient.

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Purpose The sustainability of the Lean Six Sigma (LSS) program represents the most challenging aspect for most of the organizations dealing with this methodology. In this scenario, the purpose of this paper is the description of the AMSE (which stands for Assessment, Monitoring, Sustainability, Expansion) Model, that represents a leading-edge approach to implement an effective LSS deployment on a permanent basis, by means of a structured roadmap. Design/methodology/approach The AMSE roadmap is made of four operating phases – Assessment, Monitoring, Sustainability, Expansion – it is a Model to govern the LSS deployment and to maximize both operative and economical results on a long-term basis. Findings One of the main problems of LSS programs is their sustainability (sustainability of projects and the overall program) over time; the AMSE Model allows the deployment of an LSS Governance Structure with a clear definition of tasks; this model can be effectively applied both to small and medium enterprises (SMEs) and global companies, regardless of the sector. Practical implications Both SMEs and global corporations could benefit from applying the AMSE in terms of operational efficiency, culture improvement and people engagement. Originality/value The AMSE Model represents an innovative approach for sustaining a continuous improvement culture in the organizations over time, by defining four steps (Assessment, Monitoring, Sustainability, Expansion), divided into detailed tasks, each of which is characterized by its own specific tools.

This paper provides a way to deal with issues related to design for reliability using axiomatic design (AD). A theoretical approach is studied, starting from the traditional theory of AD, in order to help designers to optimize the product's reliability using a structured approach. The aim of this work is to introduce a new method that is able to assess the product reliability using the support of the AD methodology combined with other methods, e.g. FMEA and FTA. The approach developed is called failure mode and effect tree analysis (FMETA). FMETA allows the designer to find the most critical characteristic of the product from a reliability point of view and provides the designer with a set of possible changes. The core of this work is the development of a reliability tree, used to evaluate both the RPN for the component of the product and to find the reliability relation useful for the following optimization. The reliability tree is born from the combined use of AD, FMEA and FTA. This method has been validated by an application to an automotive heavy-duty diesel engine.