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PhD Projects in Industry 4.0

Industry 4.0 is a popular topic in PhD research and hence we discuss about this topic in detail. Our team updates about this research field day by day. You will feel this, only when you read this blog.

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   PhD Projects in Industry 4.0 is a short blog that gives you about the industry 4.0 and the topics in this field. To know this, you have to get a look into this blog by now.

What is Industry 4.0?

    Industry 4.0 is an advance development in the field industry with the revolution in automation. The industry 4.0 mainly focuses of all the manufacturing machineries with wireless technologies. Also this enables the use of advance techniques in machine learning, artificial intelligence, deep learning, reinforcement learning, game theory and so on.

What are new in Industry 4.0?

     It is not just an update from previous version of industry 3.0 technologies, the industry 4.0 presents advances that are developed based on current industrial evolution. It understands the challenges and limitations in this field. 

   The field of industry 4.0 has challenges as lack of access points, not able to support large scale systems, storage of data, accuracy in the data and others. Further, the main topics in this field is given as follows.

PhD Project Topics in Industry 4.0

• Smart Manufacturing
• Blockchain Technology
• Cyber Physical System
• Redundancy Prediction and Reduction
• Supply Chain Management
• Fault Diagnosis
• Data Acquisition and Classification
• Biometric Authentication
• Task Offloading
• And Many More

Top Journal Topics in Industry 4.0

• Object Recognition and Classification
• Augmented Reality in Industrial Environment
• Smart Factory
• Cyber-Physical Production System
• Digital Twins
• Renewable Energy Generation for Industries

   PhD Projects in Industry 4.0 offers you all type of help to complete your PhD in this research field. We first get all your ideas and then make sure that we move in your interest, so that it will easier for your understanding. If you don’t have know the recent topics, then you can ask us directly and select one among it.

  We give you support from the selection of your topic to the end of thesis in PhD. We never compel you in selecting topic and continue all PhD with our assistance. Even you can prefer anyone service from us. Start you PhD Project with us and success will be at your hands.

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Industry 4.0 and Advanced Production Systems

This sub-research area focuses on advanced production systems, digitalization, and automation of manufacturing processes, with specific reference to the enabling technologies of Industry 4.0 (and subsequent paradigms).

ERC sectors

• PE8_9 Production technology, process engineering
• PE7_10 Robotics
• PE8_10 Manufacturing engineering and industrial design 
• Advanced production systems
• Computerization
• Digitalization and automation
• Additive manufacturing

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Managing Industry 4.0 holistically

The accelerated diffusion of digital technologies challenges leadership teams across all manufacturing industries. Capturing the full value of these rapid Industry 4.0 developments can only be realised by holistically orchestrating the implementation across a firm and its value network. To achieve this, it is vital for leadership teams to consider the inter-dependencies between individual activities and projects in key areas of their business, that may be as diverse as the value proposition, operational processes or value capture mechanisms – this is a complex undertaking. However, today it is not clear, how a leadership team should decide, which activities of their business model should be enhanced with which Industry 4.0 pillar and with what

Methodology

Develop a strategic decision support framework for a systematic prioritisation, which activities across a firm's business model demand 'digital' advances (including the required non-digital basics).

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• Fully Funded PhD in Industry 4.0 and intelligent future systems

  Fully Funded PhD in Industry 4.0 and intelligent future systems

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About the Programme

The Advanced Resource Efficiency Centre (AREC), based at Sheffield University Management School, is seeking applications for a fully funded PhD from exceptional UK/EU/International students with an outstanding academic record (distinction/high merit or equivalent), as well as a proven record in research training.

The UK Industrial Strategy has identified priority areas where capabilities in energy, self-driving automotive, food, construction, materials and manufacturing, robotics and Artificial Intelligence (AI), aviation, healthcare, battery technology and next generation services are to be supported in industry. This studentship will focus on advancing the understanding of how digitalisation transforms industry and future supply chain, investigating the transformation of future supply chain into intelligent future systems by exploring the role of Industry 4.0 and Internet of Things (IoT). How data will be valued, why ethics will be key, what social valuation are put upon disruptive digital technology, the co-existence model of man-machine to understand the future machine economy are also areas of investigation. The research will integrate management theories and apply technology advances to deliver new tools, and understand the societal and humanity implications fromthese advances. Possible projects may include:

• New business model and indicators for managing supply chains transition to Industry 4.0 and intelligent future systems (focus on global, cases include major industry from our existing network, data analytics and value assessment) • New forms of decision support methodology and tools for Industry 4.0 and intelligent future systems (focus on global, involves Microsoft) • Intelligent future systems: valuation of behavioural and social interactional management processes (focus on impact from autonomous vehicles, AI and robotics cases) • Data learning and Cloud-based intelligence sharing towards future inclusive autonomous resource management systems: a techno-societal transformation (focus on global, cases include social media type sentiment and AI for industry and management science of communication and decision, involvement of companies such as Microsoft and Amazon)

The supervisory team may include two of the following academics: Professor Lenny Koh, Dr Andrea Genovese, Dr Sonal Choudhary, Professor David Oglethorpe, Professor Andrew Simpson, Dr Erica Ballantyne, Dr Chantal Cantarelli, Dr Antonino Sgalambro, Dr Mike Simpson, Dr Rob Marchand, Dr Andrew Brint, Professor John Cullen, Professor Jonathan Linton, Dr Stuart Maguire, Professor Elaine Toms, Professor Panos Ketikidis. The selection of supervisors would depend on which project(s) is pursued and staff availability.

Application Process

Applicants should submit a 1000 word research proposal. The proposal should contain a brief background to the topic, which demonstrates knowledge of existing work in the field, and potential contributions to knowledge. It should also explain the proposed research methods and include a plan of the research, and a timeline.

Closing date for applications is 17.00 (UK time) on Friday 13 July 2018. Interviews will be held week commencing 6 August 2018

For more information and to submit an application, visit www.sheffield.ac.uk/management/study/researchdegrees/fundedprojects

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Home > Books > Industrial Engineering

Industry 4.0 - Current Status and Future Trends

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Published 25 March 2020

Doi 10.5772/intechopen.86000

ISBN 978-1-83880-094-9

Print ISBN 978-1-83880-093-2

eBook (PDF) ISBN 978-1-83880-086-4

Copyright year 2020

Number of pages 132

This book shows a vision of the present and future of Industry 4.0 and identifies and examines the most pressing research issue in Industry 4.0. Containing the contributions of leading researchers and academics, this book includes recent publications in key areas of interest, for example: a review on the Industry 4.0: What is the Industry 4.0, the pillars of Industry 4.0, current and future trends...

This book shows a vision of the present and future of Industry 4.0 and identifies and examines the most pressing research issue in Industry 4.0. Containing the contributions of leading researchers and academics, this book includes recent publications in key areas of interest, for example: a review on the Industry 4.0: What is the Industry 4.0, the pillars of Industry 4.0, current and future trends, technologies, taxonomy, and some case studies (A.U.T.O 4.0, stabilization of digitized process). This book also provides an essential tool in the process of migration to Industry 4.0. The book is suitable as a text for graduate students and professionals in the industrial sector and general engineering areas. The book is organized into two sections: 1. Reviews 2. Case Studies Industry 4.0 is likely to play an important role in the future society. This book is a good reference on Industry 4.0 and includes some case studies. Each chapter is written by expert researchers in the sector, and the topics are broad; from the concept or definition of Industry 4.0 to a future society 5.0.

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• Industry 4.0
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Research opportunities

We are interested to receive applications from ambitious individuals keen to pursue research interests in Industry 4.0 at The University of Manchester. Potential PhD projects include, but are not confined to, the following:

• The use of AI to achieve real time optimisation of legacy systems
• Augmented Reality (AR): AR assisted assembly of flat-pack flexible assembly stations
• Biologicalisation of manufacturing
• Injection mould 4.0
• Mobile robots for additive manufacturing
• Three-axial additive manufacturing
• Digital-twin-assisted machining monitoring
• Cloud-based monitoring of machining chatter
• Fault simulation and diagnosis of feed drivers
• Non-verbal communication with machine tool
• Virtual simulation and optimisation of extrusion-based additive processes
• Virtual modelling of near-field electrospinning
• Modelling and control of laser surface texturing
• Digitised manufacturing chain in the shop floor
• Tool wear monitoring by feed drive currents.

Alternatively follow the link below to use FindaPhD for funded opportunities:

Use FindaPhD’s filters to discover funded PhD projects that align with MACE’s areas of expertise.

Funding and further enquiries

Various sources of PhD funding are also available.

For more information on PhD project topics available that may be developed further in discussion with academics to align with your interests and expertise please see individual staff pages .

For general queries about funding and how to apply please contact the Student Recruitment and Admissions Team .

Martin Lockey Senior Postgraduate Admissions Administrator George Begg Building – B15 0161 275 4345 [email protected]

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Mechanical, Aerospace and Civil Engineering, The University of Manchester

Industry 4.0 Driven Manufacturing Technologies

• © 2024
• Ajay Kumar   ORCID: https://orcid.org/0000-0001-7306-1902 0 ,
• Parveen Kumar   ORCID: https://orcid.org/0000-0002-2922-6228 1 ,
• Yang Liu   ORCID: https://orcid.org/0000-0001-8006-3236 2

Department of Mechanical Engineering, JECRC University, Jaipur, India

You can also search for this editor in PubMed   Google Scholar

Mechanical Engineering, Rawal Institute of Engg. & Technology, Faridabad, India

Dept of Management and Engineering, Linköping University, Linköping, Sweden

• Provides case studies showing solutions from industry and society
• Integrates Industry 4.0 tools, e.g., digital twins, artificial intelligence, nature-inspired algorithms, and the IoT
• Bridges the gap between R&D in human-machine interaction for manufacturing and practical application

Part of the book series: Springer Series in Advanced Manufacturing (SSAM)

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About this book

This book is a comprehensive guide to the latest advancements in manufacturing, adopting an Industry 4.0 approach. It covers the core principles of big data informatics, digital twin technology, artificial intelligence, and machine learning strategies. Readers will gain insights into the realm of cyber-physical intelligent systems in production, the role of blockchain, and the significance of information and communication technology.

With a focus on real-time monitoring and data acquisition, the book offers practical solutions for online error troubleshooting in manufacturing systems. It explores a wide range of Industry 4.0-based applied manufacturing technologies and addresses the challenges posed by the dynamic market of production.

Recognizing the lack of a cohesive resource on manufacturing advancements within the context of Industry 4.0, the authors have taken the initiative to compile this valuable knowledge from domain experts. Their goal is to disseminate these insights with this book.

The book will be beneficial to various stakeholders, including industries, professionals, academics, research scholars, senior graduate students, and those in the field of human healthcare. With its comprehensive coverage, the book is an important reference for technical institution libraries and a useful reader for senior graduate students. 

• Intelligent Manufacturing
• Industry 4.0
• Digital Twin
• Artificial Intelligence
• Internet of things
• Cyber-Physical Production System
• Cloud Manufacturing
• Cybersecurity
• Internet-based manufacturing

Table of contents (18 chapters)

Front matter, evolution of digital twin in manufacturing application: definition, architecture, applications, and tools.

• Suveg V. Iyer, Kuldip Singh Sangwan, Dhiraj

Intelligent Feature Engineering for Monitoring Tool Health in Machining

• Debasish Mishra, Krishna R. Pattipati, George M. Bollas

Experimental Investigation of Process Parameters Effects on Extrusion Blow Molding Process Using Response Surface Methodology for Industry 4.0

• Rajendra Shimpi, Chandrakant Wani, Rakesh Chaudhari, Sarvoday Joharapurkar, Hargovind Soni, Ajay Kumar

Finite Element Analysis and Experimental Investigation of 3D Printed Biomimetic Structures

• D. L. Belgin Paul, Ayyappan Susila Praveen, V. Loganathan

Industry 4.0 in Aircraft Manufacturing: Innovative Use Cases and Patent Landscape

• Vineet Bhatia, Ajay Kumar, Sumati Sidharth, Sanjeev Kumar Khare, Surendra Chandrakant Ghorpade, Parveen Kumar et al.

Comparative Multi-criteria-Decision Making Approach for the Optimization of Abrasive Water Jet Machining Process Parameters Using MABAC

• Bimal Tamang, Satyam Sharma, Soham Das, Spandan Guha, Ajay Kumar, Ranjan Kumar Ghadai

An Empirical Analysis of Factors Influencing Industry 4.0 Implementation in Manufacturing SMEs

• Malika Aitzhanova, Dinara Dikhanbayeva, Ali Turkyilmaz, Essam Shehab

A Cost-Minimization Approach to Production and Maintenance Planning Considering Imperfect Repairs and Human Resource Constraints

• Taha-Hossein Hejazi, Donya Ramezani, Ali Golestanian

Environment-Friendly Practices for Integrating Green Business with Green Supply Chain Management: Industry 4.0 Perspectives and Beyond

• B. K. Mawandiya, Aditya Choksi, Anjaney Lokapur, Ajay Kumar, M. A. Makhesana, K. M. Patel et al.

Barrier Analysis for the Sustainable Business Practice of a Textile and Apparel Industry in Fiji Using an ISM Approach

• D. Seenivasagam, R. Ananthanarayanan, A. K. Jeevanantham, P. Kumar

Strategic Design Optimization of Cutting Tools for Enhanced Manufacturing Efficiency

• Abhishek Agarwal, Parveen Kumar, Ajay Kumar, Ranjan Kumar Ghadai

Exploring the Challenges of Integrating Lean Green Practices in Industry 4.0 Manufacturing Frameworks: An Empirical Study

• Rajesh Kumar, Rajender Kumar, Ashwini Kumar

Robotic Arm 3D Printing: Technological Advancements and Applications

• Sourabh Anand, Gayatri, Manoj Kumar Satyarthi, Pushpendra S. Bharti, Ajay Kumar, Sarita Rathee

Elephant Swarm Water Search Algorithm-Based Optimization of a Laser Beam Machining Process

• Sunny Diyaley, Shankar Chakraborty, Ajay Kumar, Kanak Kalita

Progressive Automation: Mapping the Horizon of Smart Manufacturing with RoboDK Workstations and Industry 4.0

• Mukul Kumar, Sourabh Anand, Pushpendra S. Bharti, Manoj Kumar Satyarthi, Parveen Kumar, Ajay Kumar

Improvising the Quality of Manifold Production Using Six-Sigma Technique for Implementation in Automobile Manufacturing Industries: A Case Study

• Sachin Kumar, Aman Kumar, Ajay Kumar

Digital Twin Integration for Enhanced Control in FDM 3D Printing

• Sourabh Anand, Manoj Kumar Satyarthi, Pushpendra S. Bharti, Parveen Kumar, Ajay Kumar

Intelligent Manufacturing in Aerospace: Integrating Industry 4.0 Technologies for Operational Excellence and Digital Transformation

• Vineet Bhatia, Sumati Sidharth, Sanjeev Kumar Khare, Surendra Chandrakant Ghorpade, Parveen Kumar, Ajay Kumar et al.

Editors and Affiliations

Mechanical engineering, rawal institute of engg. & technology, faridabad, india.

Parveen Kumar

About the editors

Prof. Ajay Kumar is currently serving as a Professor in Department of Mechanical Engineering, School of Engineering and Technology, JECRC University, Jaipur, Rajasthan, India. He received his Ph.D. in the field of Advanced Manufacturing from Guru Jambheshwar University of Science & Technology, Hisar, India after B.Tech. (Hons.) in mechanical engineering and M.Tech. (Distinction) in manufacturing and automation. His areas of research include Incremental Sheet Forming, Artificial Intelligence, Sustainable Materials, Additive Manufacturing, Mechatronics, Smart Manufacturing, Industry 4.0, Waste Management, and Optimization Techniques. He has over 140 publications in international journals of repute including SCOPUS, Web of Science and SCI indexed database and refereed international conferences. He has also co-authored and co-edited more than 20 books and proceedings with ELSEVIER, Springer, CRC Press, WILEY, De Gruyter, IOP, AIP and IGI Global. He has organized various national and international events including an International conference on Mechatronics and Artificial Intelligence (ICMAI-2021), International conference on Artificial Intelligence, Advanced Materials, and Mechatronics Systems (AIAMMS-2023) as conference chair. He has more than 20 national and international patents to his credit. He has supervised more than 8 M.Tech, Ph.D scholars and numerous undergraduate projects/ thesis. He has a total of 15 years of experience in teaching and research. He is Guest Editors and Review Editor of the reputed journals including Frontiers in Sustainability. He has contributed to many international conferences/ symposiums as a session chair, expert speaker, and member of the editorial board. He has won several proficiency awards during the course of his career, including merit awards, best teacher awards, and so on. He is adviser of QCFI, Delhi Chapter student cell at JECRC University and has also authored many in-house course notes, lab manuals, monographs and invited chapters in books. He has organized a series of Faculty Development Programs, International Conferences, workshops, and seminars for researchers, PhD, UG and PG level students. He is associated with many research, academic, and professional societies in various capacities. ORCID ID: https://orcid.org/0000-0001-7306-1902    

Parveen Kumar is currently serving as an Assistant Professor and Head in Department of Mechanical Engineering at Rawal Institute of Engineering and Technology, Faridabad, Haryana, India. He has submitted  Ph.D. from National Institute of Technology, Kurukshetra, Haryana, India. He completed his B.Tech. (Hons.) from Kurukshetra University, Kurukshetra, India and M.Tech. (Distinction) in Manufacturing and Automation from Maharshi Dayanand University, Rohtak, India. His areas of research include Intelligent Manufacturing Systems, Materials; Die less Forming, Design of Automotive systems, Additive Manufacturing, CAD/CAM and Artificial Intelligence, machine learning and Internet of Things in manufacturing, multi objective optimization techniques. He has over 50 publications in international journals of repute including SCOPUS, Web of Science and SCI indexed database and refereed international conferences. He has 8 national and international patents in his credit. He has supervised 2 M.Tech. scholars and numerous undergraduate projects/theses. He has a total of 13 years of experience in teaching and research. He has co-authored/co-edited several books with ELSEVIER, CRC Press, WILEY, De Gruyter and IGI Global. He is also book series editor of “Industrial and Manufacturing Systems and Technologies: Sustainable and Intelligent Perspectives” in CRC Press, Taylor and Francis. He has organized a series of Faculty Development Programmes, workshops, and seminar for researcher, UG level students. ORCID ID: https://orcid.org/0000-0002-2922-6228

Dr. Yang Liu received the M.Sc. (Tech.) degree in telecommunication engineering and D.Sc. (Tech.) degree in industrial management from the University of Vaasa, Finland, in 2005 and 2010, respectively. He is currently a tenured Associate Professor and Doctoral Supervisor with the Department of Management and Engineering, Linköping University, Sweden; a Visiting Faculty with the Department of Production, University of Vaasa, Finland; and a Chair Professor with Jinan University, China. Meanwhile, he is an Adjunct/Visiting Professor at multiple other universities. His research interests include sustainable smart manufacturing, product service innovation, decision support system, competitive advantage, control systems, autonomous robots, signal processing, and pattern recognition. Prof. Liu has authored or co-authored more than 130 peer-reviewed scientific articles and is ranked No.1 among the top authors on “big data analytics in manufacturing”. His publications have appeared in multiple distinguished journals, and some ranked as top 0.1% ESI Hot Papers and top 1% ESI Highly Cited Papers. He serves as an Associate Editor of the prestigious Journal of Cleaner Production and Journal of Intelligent Manufacturing, referees in over 60 SCI leading journals, and external reviewer for NSERC of Canada and CONICYT of Chile.  

Bibliographic Information

Book Title : Industry 4.0 Driven Manufacturing Technologies

Editors : Ajay Kumar, Parveen Kumar, Yang Liu

Series Title : Springer Series in Advanced Manufacturing

DOI : https://doi.org/10.1007/978-3-031-68271-1

Publisher : Springer Cham

eBook Packages : Engineering , Engineering (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024

Hardcover ISBN : 978-3-031-68270-4 Published: 14 September 2024

Softcover ISBN : 978-3-031-68273-5 Due: 28 September 2025

eBook ISBN : 978-3-031-68271-1 Published: 13 September 2024

Series ISSN : 1860-5168

Series E-ISSN : 2196-1735

Edition Number : 1

Number of Pages : XXI, 434

Number of Illustrations : 14 b/w illustrations, 130 illustrations in colour

Topics : Industrial and Production Engineering , Artificial Intelligence , Cyber-physical systems, IoT , Professional Computing , User Interfaces and Human Computer Interaction , Computational Intelligence

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Manufacturing

How to forge a clear path to Industry 4.0

Beth Stackpole

Oct 12, 2022

Manufacturers are counting on technologies and systems known collectively as Industry 4.0 to drive efficiencies and unleash new revenue streams in their sectors. Industry 4.0 leverages sensor technologies, advanced analytics, artificial intelligence, and machine learning capabilities to collect and analyze data.

Benefits include reducing production downtime, improving product quality, and enabling proactive maintenance.

But important factors, including legacy operations and failure to effectively engage frontline workers in operational redesign, often stand in the way of such large-scale transformation. 

Momentum for Industry 4.0 is growing — one report by Statista projects the market will swell from $263 billion in 2021 to $1.1 trillion by 2028.

Interest is surging, in part, because sensor networks are the backbone for creating feedback loops to identify hidden factories , the poorly understood processes and workarounds that drive up production costs and slow systems down.

Spending on Industry 4.0 will swell from $263 billion in 2021 to $1.1 trillion by 2028.

Yet as organizations roll out Industry 4.0, they often end up collecting data at a much faster rate than it can be utilized, according to MIT Sloan senior lecturer John Carrier.

Carrier, who teaches the MIT executive education course “ Implementing Industry 4.0: Leading Change in Manufacturing and Operations ,” argues that the biggest impediments to Industry 4.0 transformation are operations practices and legacy mindsets that keep employees tethered to familiar work patterns, despite investment in new technologies and business process innovations.

Among the core challenges are:

Lack of standardization. There are too many variations in the old ways of working, which make it difficult to discover the business processes and workflows that will reduce business risk and improve productivity.

Ghosts of old technology. When new technologies and ways of working present a challenge, some employees will go back to what is familiar. Until employees develop confidence in the new technology, they will revert to the old system when put under pressure. Value is not realized until the old ways of working are phased out.

Insufficient preparation. Companies that invest in the latest sensors and advanced software often underestimate the level of workforce training required to use those tools to improve maintenance and diagnostics. Capital-intensive systems require more preparation — the level of preparation and training should be matched to the complexity of the machinery.

A blueprint for transformation

Based on experience with industrial clients, Carrier has formulated a blueprint to avoid the trap of purchasing technology that is underutilized or doesn't deliver the intended business outcomes. He advocates for a more measured transition process that draws on systems thinking and addressing cultural norms.

This will scope lofty Industry 4.0 visions into practical strategies and manageable next steps designed to improve internal processes. Key steps include:

Focusing on critical but manageable problems that will drive initial stages of transformation. Manufacturers often install networks comprised of hundreds of sensors and only then circle back to solve a specific problem. Technology does not make problems disappear. In fact, technology can exacerbate problems by creating data overload and eroding employees' trust in the new system.

“Wiring up and fixing five pieces of equipment instead of initially wiring up 500 can be advantageous,” Carrier said. “Otherwise, you risk spending 12 to 18 months on data warehousing, sensor calibration, and maintenance before realizing improvements in performance.”

Instead of launching a full-scale network with hundreds of sensors, Carrier recommends a moderated approach that pinpoints a specific problem and harnesses Industry 4.0 capabilities to solve it. Engaging employees to reveal critical stress points in their jobs and evaluating processes to identify opportunities for improvement and value creation is essential for broader transformation.

“The system is trying to tell you where it needs help,” Carrier said. “You have to learn to listen to the system to determine where sensors are needed. Use technology to help see what is missing and engage your operators in problem-solving.”

Start with “seeing” the missing feedback loops. Knowing where to establish a feedback loop is critical to Industry 4.0’s business value, but the question is where to start. The search for hidden factories can be fertile ground, as this exercise presents an opportunity to listen to the system and identify the largest gaps. It is also important to put processes in place that reduce the time from measurement to action. Collecting data that sits in a database or spreadsheet is insufficient to drive change.

For example, Heineken Mexico applied learning from this approach to solve a bottleneck at its production plant .

Sequence in technology adoption while removing unsustainable current systems. Deploying new technologies like sensors, cloud platforms, and advanced algorithms can empower workers with new insights. But as soon as they run into problems or encounter systems that are complex and unwieldy, they are going to revert to old systems and traditional ways of working.

By introducing tightly scoped and incremental Industry 4.0 initiatives, workers can more easily digest new systems and adjust to new work patterns. At the same time, it is important to remove old systems to eliminate fallback possibilities. Subtraction is harder than addition, and leaders must provide the space and time for their employees to incorporate the new technology and redesign their work.

Executive education Dec 12 – 14 2022: Implementing Industry 4.0

Related Articles

PROFESSIONAL CERTIFICATE PROGRAM IN

Industry 4.0, the path to success in the 4th industrial revolution.

Organizations operate in an environment that is technologically and competitively evolving more rapidly than ever before. As such, they continue to redesign their product operations, business models, and customer support solutions. Until now, industry has sought profitability in standardization, series production, large volumes, and cost reduction.

Now, organizations must adjust to this disruptive market leveraging technology to drive growth and efficiency. New technologies are a game-changer, as they allow greater product customization breaking fixed structures from factories, making products more modular, and generating profits despite producing fewer products.

Organizations that engage in intense management practices and technology deployment can improve asset efficiency by 10-20%.

Source: Deloitte analysis

Additive manufacturing (processes that make three-dimensional products from a digital design) can reduce material costs by up to 90% and energy costs by up to 50%.

Source: World Economic Forum

The use of integrated processes in healthcare systems in an economy of scale enables cost reduction by 15-30%.

Source: Strategy& PWC

An online Professional Certificate Program to boost performance through disruption

From leading technologies such as the internet of things (IoT) and artificial intelligence to understanding the fundamentals of smart manufacturing and product platforms, through the Professional Certificate Program in Industry 4.0, we prepare professionals to tackle these challenges head-on and provide them with the knowledge and tools to succeed in the digital age.

The objective? To help them bring to their organizations:

Greater Efficiency by learning how to optimize product processes

Maximum Impact by learning about technology management

In this tailored program, participants will be able to learn about the technologies and tools most applicable in today’s industry directly from leaders in the sector who are pioneering change.

LEARN MORE ABOUT THE PROGRAM SPECIFICS

The learning journey.

For twelve months, and in a completely online format, we guide participants through the five courses that will influence and help them carry out their own industrial revolution:

Management of Technology II: Strategy & Portfolio Analysis

• Machine Learning: From Data to Decisions
• Digital Platforms: Designing Two-Sided Markets from APIs to Feature Roadmaps

Forecasting Technology Innovation: Using Data for Strategic Advantage

Leadership & Innovation

• Women in Leadership: Becoming an Agent of Change

The skills you will develop

By studying and passing the five courses that are part of the Professional Certificate in Industry 4.0, you will be able to develop:

Understand the evolution of the industry

from craft manufacturing to mass customization.

Leverage platforms for identifying new market

and product opportunities to generate revenue growth.

Identify major contemporary methods

and tools for product family and platform design.

Explore emerging trends in smart manufacturing

and visualize production data to better understand key variables and underlying phenomena in a manufacturing environment.

Delve deeper into machine innovation and machine vision,

working through different iterations of a fiber extrusion device (FrED), specifically designed to provide program participants examples of how to optimize machines.

Carry out advanced data analysis

using data sets produced on FrED in a manufacturing setting.

Apply the theory behind the IoT+

to construct real applications and improve them using smart technologies.

Learn to quantify technological progress over time

using relevant figures of merit (FOMs), and map one or more technologies to a target product and/or service of their choice and set realistic FOM-based targets.

Develop strategies, cultures, and structures

from a leadership perspective that foster creativity and innovation.

In addition, you will receive a Certificate of Completion

All the participants who successfully complete Industry 4.0 will recieve a Certificate of Completion from MIT Professional Education. Furthermore, the participants who complete the program recieve Continuing Education Units (CEUs)*.

To obtain CEUs, complete the accreditation confirmation, which is available at the end of the course. CEUs are calculated for each course based on the number of learning hours.

* The Continuing Education Unit (CEU) is defined as 10 contact hours of ongoing learning to indicate the amount of time they have devoted to a non-credit/non-degree professional development program.

To understand whether or not these CEUs may be applied toward professional certification, licensing requirements, or other required training or continuing education hours, please consult your training department or licensing authority directly.

This Professional Certificate Program is aimed at

• PLANT MANAGERS and Product managers.
• PRODUCT LINE STRATEGISTS, PLATFORM ARCHITECTS, R&D engineers, and systems engineers in industrial and government contexts.
• DESIGN AND MANUFACTURING ENGINEERS seeking to learn about data and modeling in a manufacturing environment.
• DATA SCIENTISTS looking to apply their craft to the growing field of smart manufacturing.
• CONSULTANTS who want to add value around the latest technology transformations in manufacturing.

A CLOSER LOOK AT THE PROFILE

• Professionals who want to obtain a broader strategic vision about how methodologies, technologies and tools can transform their operations.
• Also, those who are interested in understanding how to define modular and scalable product architectures, utilizing standardization, customization, and platform leveraging strategies to maximize cost savings.

Meet the instructors of this program

Listed in alphabetical order .

DIRECTOR OF THE MIT MASTER OF ENGINEERING IN ADVANCED MANUFACTURING AND DESIGN. ASSOCIATE DIRECTOR, MIT.NANO.

Dr. brian w. anthony.

"Using technology to refine the manufacturing process allows us to offer better products in the market, faster and more economically".

Dr. Anthony is director of the MIT Master of Engineering in Manufacturing Program, co-director of the Medical Electronic Device Realization Center and deputy director of the MIT Skoltech Initiative. He possesses more than 20 years of product realization experience and has won an Emmy from the Academy of Television Arts and Sciences for his innovations in broadcast technology. Dr. Anthony designs instruments and techniques to monitor and control physical systems. His work involves the analysis and the design of systems. He also uses mechanical, electrical and optical engineering as well as computer science and optimization to develop solutions.

Dr. Anthony´s research revolves around the design of instruments and techniques for measuring and controlling complex physical systems and includes the development of instruments and measurement solutions for manufacturing, medical diagnostics, and imaging diagnostics. In addition to his academic work, he has extensive experience in market-driven technological innovation, product development and entrepreneurship, and marketing at the point where information technology and advanced manufacturing come into contact. As a teacher, his main interests are the modeling of large-scale systems in a variety of areas involving decision making and the development of optimization algorithms and software useful for analyzing and designing these types of systems. He is an expert in market-driven technological innovations, as well as in entrepreneurship.

DIRECTOR, SYSTEM ARCHITECTURE GROUP AT MIT

Dr. bruce cameron.

"Digital platforms are some of the most interesting (and hardest!) technical challenges to work on today."

Dr. Bruce Cameron is director of the System Architecture Lab at MIT and co-founder of the consulting firm Technology Strategy Partners. His areas of research include technology strategy, system architecture and product platform management. Previously, Dr. Cameron led the “MIT Commonality”, a research study of 30 companies on platform performance, which concluded that companies face systemic pressure on homogeneity, in part, as a result of problems in determining costs. Dr. Cameron has supervised more than 50 graduate students and conducted research projects for Amazon, BP, Sikorsky, Nokia, Caterpillar, AMGEN, Verizon and NASA.

Dr. Cameron teaches the subject of System Architecture for the “System Design and Management”, where he has trained over 500 students. Dr. Cameron´s teaching at Sloan Executive Education has been rated as the highest level of Executive Education program at MIT for several years. In addition, he is the Faculty Director of MIT´s online certificate “Architecture and System Engineering”, which has trained more than 5,300 participants.

PROFESSOR OF AERONAUTICS, ASTRONAUTICS AND SYSTEMS ENGINEERING AT MIT

Prof. olivier de weck.

"The design of platforms and product families is aimed at achieving long-term success and survival of companies".

Olivier de Weck was born in Switzerland and has a degree in industrial engineering from the ETH Zurich and in aerospace systems engineering from MIT. Prior to joining MIT, he was an engineering liaison and later director of the McDonnell Douglas F/A-18 aircraft engineering program.

Professor De Weck is a leader in systems engineering research. He focuses on the design of complex man-made systems, such as aircraft, spacecraft, cars, printers and critical infrastructure, and on their evolution. His main focus is on strategic properties that have the potential to maximize life cycle value. Since 2001, his group has developed new methods and quantitative tools that explicitly consider production, flexibility, common features and sustainability, among other characteristics. Professor De Weck’s teaching emphasizes excellence, innovation, and the combination of theory and practice.

SENIOR LECTURER IN THE DANIEL J. RICCIO GRADUATE ENGINEERING LEADERSHIP PROGRAM AT MIT

Dr. david niño.

"Leaders learn to find important problems but define them in such a way that allows a team to come together to solve them".

EXECUTIVE DIRECTOR OF MIT'S GEOSPACIAL DATA CENTER

Dr. abel sanchez.

"Five technologies are redefining both the way we make our products and the types of opportunities that exist in the marketplace".

Dr. Sanchez is the architect of the global network “The Internet of Things” and data analysis platforms for SAP, Ford, Johnson & Johnson, Accenture, Shell, Exxon Mobil and Altria. In cyber security, he has developed cyber-attack impact analyses for the U.S. Department of Defense and a password firewall for the IARPA.

Dr. Abel Sanchez holds a PhD from the Massachusetts Institute of Technology (MIT) and teaches MIT courses in cyber security, engineering, blockchain and data science. He has been involved in developing educational software for Microsoft and establishing the Accenture Technology Academy. He has produced over 150 educational videos, has 10 years of experience with learning management systems and has made deployments in the Americas, Asia and Europe.

PROFESSOR OF MECHANICAL ENGINEERING AND INDUSTRIAL ENGINEERING

Prof. timothy w. simpson.

"Courses often don’t ask the question,‘How can we really design and take advantage of these processes?’ and that question drives my courses."

Timothy W. Simpson is a professor of mechanical and industrial engineering at Pennsylvania State University. He holds senior positions in technical design and in the Faculty of Information Science and Technology. His research areas include product family design and platform-based product development, multidisciplinary design optimization, commercial space exploration, and additive manufacturing. He has published over 250 articles in peer-reviewed journals and conference proceedings. He is the senior editor of two books, ‘Product Platform and Product Family Design: Methods & Applications’ (2005) and ‘Advances in Product Family and Product Platform Design: Methods & Applications’ (2013). His research has been supported by federal and state agencies such as NSF, ONR, DARPA, EDA and DCED, as well as numerous companies ranging from startups to multinationals.

He has worked with more than 30 different companies to apply his methods of product line improvement and product development practices. He helped establish and manage the Product Platform group on LinkedIn.

DIRECTOR OF THE MIT GEOSPATIAL DATA CENTER

Prof. john r. williams.

"Once you climb that first mountain of knowledge, you will be able to teach yourself many things".

Professor John R. Williams’ research focuses on the development and application of computing algorithms in distributed cyberphysical systems. He was director of the Auto-ID Laboratory, where the Internet of Things was invented. He is considered, along with Bill Gates and Larry Ellison, one of the 50 most powerful people in “Computer Networks”.

He is author and coauthor of more than 250 articles in journals and conferences. Professor Williams teaches courses on the basics of programming, modern software development, the architecture of web, cloud and blockchain systems. In addition, he holds a BSc in Physics from Oxford University, an MSc in Physics from UCLA, and a PhD from the University of Swansea.

JOHN E. BURCHARD PROFESSOR OF HUMANITIES AND CO-CHAIR OF THE GENDER EQUITY COMMITTEE OF THE SCHOOL OF HUMANITIES, ARTS, & SOCIAL SCIENCES, MIT - CORDINATING INSTUCTOR OF THIS COURSE

Prof. edward schiapa.

Prof. Edward Schiappa is the former head of comparative media studies/writing and is MIT’s John E. Burchard Professor of the Humanities. He conducts research in argumentation, persuasion, media influence, and contemporary rhetorical theory. He has published 10 books, and his research has appeared in Philosophy & Rhetoric, Argumentation, Communication Monographs, and Communication Theory.

PROFESSOR IN THE DEPARTMENT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCE AT MIT

Prof. devavrat shah.

Devavrat Shah is an Andrew (1956) and Erna Viterbi Professor of the Department of Electrical Engineering and Computer Science at MIT and the faculty director of the MicroMasters in Statistics and Data Science program with the MIT Institute for Data, Systems, and Society. He also is a member of the Laboratory for Information and Decision Systems (LIDS) and the Operations Research Center (ORC) at MIT. He currently directs the Deshpande Center for Technological Innovation at MIT.

His current research interest is in developing large-scale machine learning algorithms for unstructured data, with particular interest in social data. He has made contributions to the development of “gossip” protocols and “message-passing” algorithms for statistical inference that have been pillars of modern distributed data processing systems.

He cofounded Celect, Inc., which has been part of Nike since 2019. In 2019, he cofounded Ikigai Labs with the mission of building self-driving organizations by empowering data business operators to make data-driven decisions with the ease of spreadsheets.

PROFESSOR, INSTITUTE FOR DATA, SYSTEMS, AND SOCIETY, MIT

Prof. jessika trancik.

Jessika Trancik is a professor in the Institute for Data, Systems, and Society at the Massachusetts Institute of Technology. Her research examines the impacts of technologies and the reasons behind technological change. She has developed theory and predictive models to understand why some technologies improve faster than others, and what technology features enable rapid innovation. Trancik has developed models for forecasting technological change, which inform engineering design, public policy, and investment portfolios. Several of her theories and models have been applied to new and developing energy technologies, such as solar energy and batteries, and to electricity and transportation systems. Her models have also been used to inform government innovation policy, and applied in diverse industries, including finance, healthcare, manufacturing, software, and consumer products. Her work has been published in journals such as Nature, Proceedings of the National Academy of Sciences, Nature Energy, Nature Climate Change, and Environmental Science and Technology, and has been featured by news outlets such as the New York Times, Washington Post, Financial Times, and NPR.

Three blurbs:

• Professor Trancik received her B.S. from Cornell University and her Ph.D. from the University of Oxford as a Rhodes Scholar.
• She has developed theory and predictive models to understand why some technologies improve faster than others, and what technology features enable rapid innovation.
• Her models have also been used to inform government innovation policy, and applied in diverse industries, including finance, healthcare, manufacturing, software, and consumer products.

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