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In the very present moment, every fiber of the worldwide manufacturing fabric is under threat since we are in the midst of a perfect storm. This storm is the Industry 4.0 revolution that is and will be disrupting the long-establish industrial practices. The core feature that makes this industrial revolution so pervasive is the fact that it stems from a combination of nine technologies. If introduced individually, their impact is meager but when connected in the appropriate manner, their full potential is untapped. Yet, not all that comes with this new scenario are advantages, it also comes by hand with an in-crease of the complexity in managing and designing industrial facilities since all these newcomer technologies must be intertwined in the proper way. Therefore, stronger emphasis must be placed on how these technologies are taught in the university environment as, more than often, university gradu-ates are the ones that bring new praxes into their labor world. Problem-based learning (PBL) mainly relies on using complex real-world problem to drive students learning and boost the knowledge transfer. When PBL is coupled with discrete event simulation (DES), synergies are created, and students are able not only tackle real-world problems but also to experiments within an immeasurable number of scenarios. Therefore, this thesis aims to investigate and propose a practical application case which can be used Politecnico di Mi-lano’s Industrial technologies course based on simulation technologies to in-crease students’ engagement and better prepare them for the real-world. To reach such a goal, first, a literature review was undergone following a struc-tured methodology. Second, relying upon I4.0 lab as a real system in which the case study is built upon, a five-steps methodology was used to create the application case study. Outgoing

The objective of Manutelligence platform is to manage manufacturing intelligence; all data, information and knowledge related to the Product Service (PS) and its lifecycle. The platform is based on two existing platforms and some analysis tools (for example LCA and LCC). It was developed according to the needs of four use cases in different industrial fields (automotive, ship, smart house, 3D-printing). The chapter describes the four-phase methodology to define the common aggregated requirements for the platform. The phases include requirement elicitation, structuration and organization, analysis and refinement and validation. In the elicitation phase the requirements were identified from the use cases, in the structuration and refinement phases they were further consolidated, categorized and processed towards aggregated requirements and in the validation phase the resulting aggregated requirements were compared to the original use case requirements. The chapter also shows the main results of each phase.

In the recent years, Product Service Systems (PSSs) and smart products are surging in the market and acquiring a strategic role for companies’ survival. Their relevance is constantly pushed by technological progress, increased customers’ demand for always different functionalities and manufacturers’ need for improving their position on the market. Manufacturers, compelled towards the transformation process into PSS providers, have to face the challenge of building up knowledge for successfully providing such complex solutions, also resorting to the help of more effective IT systems and tools. The need to adopt a collaborative design platform, typically used in product engineering processes, is starting to be raised also in the PSS context, since manufacturing companies often have a lack of knowledge for providing PSS. This work, grounded on a combination of Lean and DfX-based theories, is aimed at contributing to improve the knowledge formalization and sharing with the support of IT tools. In this sense, a tool able to manage PSS design knowledge, the Lean Content Design Guidelines and Rules generated and referring to the Design for Product Service Supportability (DfPSSu) approach, is proposed. Finally, to fully exploit design knowledge through a structured engineering workflow, the Lean Design Rules tool (LDRT) is integrated in a more holistic engineering environment able to interact with Product Lifecycle Management (PLM) systems.

This thesis aims to widen a Methodology, based on the principles and techniques of Lean Thinking, which allows Companies to improve their Product Development processes into a methodology that also improves the service development process. It tries to give an answer to the Companies need to review and optimize their Product-Service development processes affected by constantly changing markets and increasingly complex customers. The Methodology proposal is a result of the work of previous colleagues that was originated from the Lean Thinking techniques and their application in Product Development field. Afterwards, it has been adapted and tested by carrying on some “on the field” experiences with business subjects who have provided key knowledge to its refinement. The Methodology seeks at continuous improvement of the Product-Service Development processes which are consonant with the context in which Companies operate. This means that when a corrective action is carried out it cannot be exclude from future analysis because maybe in those future analysis the change is a waste. This also fits with the Lean perspective that put the constant research for perfection as one of its pillar. For the same reason it is a recursive Methodology compound by five steps, that go from the systematic identification of waste in PSD process, to their removal, until the introduction of targeted corrective actions. Those steps are: 1. Waste Identification & Evaluation. The starting point to develop this phase is an existing list of waste likely to be found in NPSD processes and a Priority Index (PI) to evaluate them. This phase is the one widened so as to include and include the service into the product development analysis. 2. Waste Prioritization. On the basis of the PI, in this phase wastes are put in a priority order and the first to be removed are chosen. Beside this, in association to them also potential detection ways and corrective actions are defined. 3. Sub process identification. It consists in the determination of the sub process affected by the main wastes and so to be improved. 4. Sub process analysis. This phase deals with the sub process analysis to find the critical and eliminate them. Also in this phase several alternative methods have been proposed, with a deepening on Value Stream Analysis and Map. 5. Corrective Actions. In this phase, the correctives actions to be implemented are chosen according to the effort required and the effect that they produce, PICK matrix as a tool is suggested. 2 To test the previous steps listed and also to acquire some feedback about the rightness of the methodology, two cases were conducted. On the one hand, the 5 steps were applied in the car sharing company Car2go which is a very clear example of a product-service. On the other hand, the Politecnico di Milano involvement in Manutelligence consortium gave the opportunity to be in touch with Fundació CIM (based in Barcelona) which manages several Ateneus of Digital Fabrication. These ADFs are places where everyone can go with an idea and transform it into a prototype. Thanks to this collaboration, it was provided another case study with different level of servitization (compared to de Car2go one) on which to perform the first full application of the Methodology. As a result, these activities have highlighted the forces of the Methodology that are its intuitiveness, short implementation time and easy to implement by people without experience, after a brief introduction to Lean Thinking and its techniques. At the same time, several limits have been found and accepted as starting points for future researches and insights. The thesis is structured in the following Chapters:  Chapter 1, Product-Service Systems: This is the opening Chapter, it provides an overview of the context in which the work has been developed, focusing in particular on the current importance of Product-Service Systems. In addition, it explains the objectives and the structure of the thesis are stated.  Chapter 2, Tools and Methodologies for LPSD process: State of the Art: This Chapter is a deep analysis of literature on Lean, by exploring its principles and technique and it shows the state of the art as regards to their application in Product-Service Development context.  Chapter 3, The proposed methodology: In this Chapter is shown the initial methodology in which is based the new one and a guide to its implementation is provided. Then, the additions to it are explained and the process to get to them is detailed.  Chapter 4, Business Case Application: It exposes the business cases of Car2go and ADF giving complete examples of Methodology implementation.  Chapter 5, Conclusions: This is the final Chapter where a summary of the methodology analysis is given and suggests future researches and investigations.

The European research project AmI-MoSES is focused on developing energy enhancement service solutions for SME manufacturing companies. The planned service concept is based on Energy Key Performance Indicators in the form of Energy Use Parameters (EUP). EUP indicators are based on monitored energy consumption data (ECD), other measured data and related energy use context showing in a detailed way how energy was used. Case study illustrates how to define EUPs for natural gas fired furnace for steel bar preheating process. The results are visualised with an advisory system to assist users in decision making with regard to energy efficiency improvements and optimisation.

Literature review on the state of the art of the related topics: Lean Thinking, New Product Development, Visual management. -Indedit Business Case: Application of acquired knowledge in the literature in the INDESIT Company's production process. -Analysis of the results. -Discussion and conclusion. Outgoing