Descrizione del corso

Industry 4.0: a chance for operational excellence (Prof.ssa Natalia Trapani – Università di Catania)

Operational Excellence is a term used in high-performance organization to identify the approach used to align the corporate strategy with the corporate vision. Implementing the operational excellence is mandatory for companies’ competitiveness in Industry 4.0.

Industry 4.0 promised disruptive transformation of business competitiveness based on Industrial Internet of Things (IIoT), Cyber-Physical Systems (CPS), and Social Computing in order to obtain a significant improvement in the performance of complex systems through real-time monitoring and knowledge management.

Industry 4.0 is not restricted to the production system but it extends to value creation along the entire supply chain and business network. This requires a deep transformation of business models in manufacturing and service companies, in order to manage:

– complexity and flexibility, due to a new “mass customization” approach (i.e., higher variety in products and smaller lot sizes);

– interoperability, because highly connected networks require systems able to communicate with each other;

– virtualization, a “digital twin” of the physical manufacturing process allows the real world modelling and simulations;

– big and smart data analysis; real-time capability, i.e. decisions are no longer based on “historical data” but on “real-time data”;

– service orientation, the tendency to provide services more than products require the integration along the value chain from supplier to customer.

New technologies cannot be the aim but only a means to reach operational excellence: the technological evolution is the key enabler for operational excellence. The fourth industrial revolution is building on previous advances and, in order to obtain advantages from new technology, the previous one has to be implemented properly. The integration of Industrial Internet of Things (IIoT) with wearable technology and augmented reality allows development and transformation in maintenance management and execution, energy management, quality monitoring, knowledge management, training of the workforce and assisting in complex operations.

It is crucial That researchers develop new frameworks, new tools, and new methodology to Obtain agility in manufacturing and adaptability to customer needs, business continuity and equipment availability, process stability and quality, efficiency in economic, human, energy resource use and reduction in environmental impact, and a new set of KPIs to support (and supported by) real-time monitoring and analysis.

Also, this requires new skills in data handling expertise, advanced analytics strategic development, integration of engineering, management, and information technology competencies in order to manage processes which are more and more automatized and complex.

Italian point of view on Industry 4.0 and technological priorities for the countrywide system (Dr. Stefano Ierace – Consorzio Intellimech)

Industry plays a central role in the economy of the European Union, accounting for 15% of value added (compared to 12% in the US). It serves as a key driver of research, innovation, productivity, job creation, and exports. Industry generates 80% of the EU’s innovations and 75% of its exports. Including its effect on services, industry could be considered the social and economic engine of Europe. Yet European industry has

lost many manufacturing jobs over the last decade, and is facing tougher competition from emerging markets. The ghost of “deindustrialization” currently haunting European governments and the European Commission is galvanizing them into action. In this scenario, the political Institutions promoted several actions at different level to promote manufacturing and increase its competitiveness. Smart Manufacturing, Industry 4.0, Intelligent Factory: all these terms are strategies to increase the value added derived from this activity.

The presentation will show the Italian scenario within the Industry 4.0 context. More in detail, due to the characteristic of industrial ecosystem (SMEs instead of Large Enterprise), the strengths and weaknesses of the introduction of new technologies will be analysed. Moreover, also considering the initiatives at national level such as Intelligent Factory cluster, the technological priorities for Italian industry will be shown. Also the approach used to define these priorities will be discussed considering the relationship between industry and academia and the priorities in industry matched with research ones.

Lean Manufacturing in Industry 4.0 (Dr. Daryl John Powell – Kongsberg Maritime)

Daryl Powell is the Lean Programme Manager at the Subsea Division of Kongsberg Maritime in Norway. He is also an adjunct professor at the Norwegian University of Science and Technology, where his research focuses on Corporate Lean Programmes and Network Action Learning. Drawing on his extensive background in the field of Lean Manufacturing and Lean Management, Dr. Powell shares practical insights into what we might expect of things to come for lean in the fourth industrial revolution. Smart automation, digitization and internet of things are just a few of the concepts that present an array of interesting opportunities for further development of the lean paradigm. Powell also reveals some of the exciting developments that are currently unfolding in what Norwegians refer to as Norway 6.0.

Human Factor in the Industry 4.0: new design procedures and innovative technologies (Dr. Ing. Martina Calzavara – Università di Padova)

Despite the opportunities the automatization of industrial and logistic systems offers, many companies still rely on human work in many areas. Most planning models that have been proposed in the past to support managerial decision making in industrial and logistic systems have neglected the specific characteristics of human workers, which often led to unrealistic planning outcomes or work schedules that may even be harmful to workers employed in the system. To guarantee a high level of productivity and efficiency and to make sure that decision support models reflect reality as good as possible, it is necessary to consider human factors in addition to economic aspects in designing industrial and logistic systems. Even though recent research has started to integrate human factors issues into decision support models – for example by modelling learning effects or human energy expenditure –, there still seems to be a large gap in the literature concerning the development of decision support models for industrial and logistic systems that take account of the interaction between the human worker and the work environment. The latter can, to a large extent, be influenced by the system designer.
Generally, human factors (perceptual, mental, physical and psychosocial aspects) determine the performance of industrial and logistic systems to a large extent if human operators are employed. This aspect becomes more challenging in light of demographic changes, which will likely put human factor-related issues in logistics – such as the risk of developing musculoskeletal disorders in labor-intensive work environments, for example – on top of the agendas in many companies. In addition, the consequences of using innovative technical solutions to support industrial and logistics processes, such as augmented reality or motion capturing, is not yet fully understood in light of human performance and errors. This session aims at investigating the development of innovative approaches for the integration of human factors in industrial and logistic system design.

National plan Calenda 4.0: implications of hardware and interconnection (Ing. Micaela Caserza Magro – SedApta)

Industry 4.0

the evolution of production
added value in production industries
the role of the technology
the basic concepts and short glossary
requirements for the value chain
manufacturing flexibility

The pyramid of automation

Basic requirements

System integration

Basic requirements

Platform Industrie 4.0: RAMI 4.0

Industrial Internet Consortium

I3C (Industrial Internet Interoperability Coalition)
IIAF (Industrial Internet Architectural Framework)
IIAR (Industrial Internet Architectural Representation)

Industrial Internet of Things (IIoT) Three-Tier Architecture

FIELDCOMM GROUP

FDI Device Packages; The Core of FDI; Edge devices; OPC UA Server

Digital Factory

Piano Nazionale Industria 4.0

Enabling technologies for Industry4.0

National Calenda plan for Industry4.0

Instrumental object – PLC based control
Instrumental object – Basic requirements
Instrumental object – additional requirements 2 – oo – 3
Interconnection
Logistic system integration 1 – oo – 3 – Option 1
Logistic system integration 1 – oo – 3 – Option 2
Remote maintenance–Remote disgnostic–Remote control
Monitoring and adapation to the process drifting

Cyber physic system

IoT in Industry 4.0 (Eng. Filippo Torriani – Abo Data)

Abo Data describes how some customers who have chosen in recent years IOT solutions, and through IOT leverage, have been able to anticipate the business needs of the new digital world.

Innovative marketing,
New customer and market share,
From product sales to service sales,
Pay as you growth.

Real success examples in the fields:

“Connected product”; Coffee machines; “connected tires”
Connected Factory “energy control”, world automotive manufacturer.

Digital innovation and transformation for factories in Industry 4.0 (r)evolution (Prof. Flavio Tonelli – Università di Genova)

In recent years manufacturing companies have been faced with different challenges, in particular with an increasing level of variability. The variability implies a different set of dimensions such as demand, volume, process, manufacturing technology, customer behaviour and supplier attitude, transforming industrial systems engineering domain. This trend is now even accelerating with a direct impact on the value chain and related physical supply chains as well as factory design and management. Several national strategies and new technological roadmaps, such as the German high-tech strategy “Industrie 4.0” or the Italian cluster “Fabbrica Intelligente”, aim at approaching this transformation enhancing the flexibility and re-configurability of current manufacturing systems among many other competitive dimensions; new emerging and potential enabling technologies could allow a next generation of manufacturing systems towards real implementation of smart factories. This speech introduces technological concepts of Industry 4.0 and related enabling technologies (such as Cyber-Physical Production Systems (CPPS), the Internet of Things, and the Internet of Services) that could support decentralization and manufacturing flexibility. Their application allows to orchestrate and execute manufacturing and production processes with the aim of supporting individualized production, small lot sizes, small batches and provide advanced decision support. The final research aim is to identify and define digitalized opportunities for specific type of flexibility that has an impact on the manufacturing system starting from an analysis of potential improvements of current Manufacturing Execution Systems (MES). For each flexibility type (variant spectrum, expansion, scheduling and volume), the scope is to demonstrate the principal contributions expected by using specific use cases described in terms of process improvement. The identified flexibility type in manufacturing systems are discussed and contrasted with the various reconfiguration use cases, which include specifically the planning, orchestration, and optimization of production processes within MES. Finally, the use cases presented by these manufacturing paradigms are discussed in order to demonstrate how far decentralization and self-organization can be driven to the achieving Industry 4.0 key requirements.

Smart Manufacturing in the Factory Life-Cycle (Prof. Marco Macchi – Politecnico di Milano)

The speech will provide a perspective of Industry 4.0 current potentials in the scope of the Factory Life-cycle. Use cases will regard the Begin of Life and Middle of Life (BOL and MOL), having a special focus to virtual commissioning of industrial plants and manufacturing operations management. The role of semantic data models will be discussed as lever for enterprise interoperability at the MES level and beyond. Once interoperability is guaranteed, Cyber-Physical Systems will be seen as a leading concept to push the transformation towards the use of simulation and predictive capabilities in manufacturing systems.

Industry 4.0: Siemens’ vision (Eng. Andrea Loleo – Siemens)

The aim of the speech is to give an overview of Siemens’ vision within industry 4.0 with particular attention to digitalisation issues.

In the future vision of manufacturing, the whole set of people, machines, and devices will create production environments completely different in respect of today. Producers, institutions, universities and research centers are working together to analyze and apply this vision, which was initially promoted by the German initiative “Industrie 4.0”.

The main innovative forces can be identified as follows:

Faster, more efficient and flexible production.

In the near future, millions of machines, systems, sensors will be interconnected by sharing information. This “global” network will not only allow companies to produce more efficiently but will provide the necessary knowledge to increase production flexibility in response to more and more specific demands from the market.

Digital Twins.

The physical world will increasingly have an equivalent digital twin. Siemens PLM Software is a clear example of how this concept can be implemented. The software is used intensively to design and test processes and products before that even a single physical element (machine, assembly line, PLC) is produced or purchased.

Self-organized factories.

Information technology and manufacturing will increasingly be one thing. Although it is difficult to predict precisely how the “smart factories” will be in the future, some scenarios can already be outlined: for example, machines can organize themselves according to their availability and capacity, in order to always ensure the best configuration for obtaining the maximum efficiency and productive flexibility.