Evolutionary developments and the Problem statement

If we look at the past three Industrial revolutions of 18^th, 19^th and 20^th centuries, from Steam to Electricity to Computing, these all were directed towards improving efficiency and speed of the processes in which humans were involved. And the fourth Industrial revolution of 21^st century, denoted as I 4.0, is no different except that it deals with multidisciplinary technologies and the context of high aspirations of the society, rendering the realization to be much more complex and challenging.

Factors that have contributed to evolution of I 4.0 can be summarized as below:

• 21st Century is seen as a watershed in technology developments and innovation that have touched human lives in many ways
• Greater demand of Industry of today is cost and energy savings and increase in operational efficiencies
• There has been a continuing search to seek elegant & robust solutions to the needs of the Industry and Society
• Technologies are accessible to play a pivotal role in the search of such solutions, and their effective deployments
• Continuing focus on Industrial Automation
• Need to address environmental pollution and increasing urbanization

The Project I 4.0 that was conceptualized a decade ago with a high tech strategy of German Government to promote computerization in manufacturing, is seen expanding its scope to a much bigger dimension necessitated by factors such as;

• Enhance : Enhance Operational productivity - use data insights, instrumented with IoT, with fewer disruptions
• Optimize : Optimize Supply Chain - smart supply chain, uncover hidden insights, transform outdated processes, deliver superior customer experience
• Improve : Improve Worker Safety - avoid loss in health care costs, use wearable and environmental sensors

Consequently, the concept is taking form of a much larger and an integrated system described as :

‘Information Intensive transformation of manufacturing, and other industries, in a connected environment of data, people, processes, services, systems and IoT enabled industry assets, with generation, leverage and utilization of actionable information as a means to realize smart industry and eco system of industrial innovation and collaboration.” (Wikipedia)’

The four pillars of this transformation are :

• Connectivity : Ability of machines, devices, sensors and operators to communicate in real time and to interconnect
• Data : Info transparency - use of data by operators and machines that enable to get insight and support decisions
• Automation : Technical Assistance – ability to carry out tasks otherwise difficult or drudgeries for humans (Robots)
• Intelligence : Decentralized decisions - ability for simulation and predictions and decisions support & reporting in an automated environment that augment human intelligence

Solutions/Technology implementations

So, what are the drivers for this transformation to take place ?

It is indeed the technologies, the associated environments and the organizational regulations that are driving this transformation, conceptualized a decade ago, to serve the society.

The constituent technologies of I 4.0, as the enabling drivers, that are primarily responsible for building solutions are :

• Astonishing rise in Data Volumes : As per the IDC estimates, data that lately has been increasing at 40 % year on year, has a current store of 44 zettabytes, and is likely to cross 163 zettabytes by the year 2025. This data with its volume, velocity, variety and also veracity and value, presents a great wealth for Businesses to monetize. Cloud makes it possible to access huge data and applications that source this data, to turn the data into information and use that information to generate insights and implement those insights to monetize this data in real time for the benefit of the industry.
• Significant rise in Computing Power : Today’s computers present super power like never before, going upto several hundreds of Petaflops and extremely low inter- processor communication latencies. It makes simulation and modelling possible for complex environments such as weather prediction, seismic data processing, genomic sequencing, drug discovery, urban environmental modelling, complex encryption and decryption, statistical analyses in number crunching applications, and cognitive computing for intelligent data analysis and decision support, each of which has relevance to the society.
• Artificial Intelligence : Together with machine learning make it possible carry out business intelligence through use of mathematical tools/statistical analysis to unearth trends, and further analytics to draw inference and predict the events to happen. It captures all the three stages of data handling; Analysis (using machine learning and natural language processing tools), Processing (using business intelligence tools and cloud computing) and Visualization (for reporting and displays). It has accordingly opened opportunities to serve enormous (data prime) sectors such as HealthCare, Education, Farming & Agriculture, Banking & Finance, Insurance, Retail & Supply Chain and Manufacturing. These have direct bearing to service humanity, and have been dealt with in detail in several reports elsewhere.
• Robotics & Automation : This technology has been in existence for many years, though in limited use, mostly in areas where safety to humans are involved or used for industrial automation. With the evolution of AI, the power of predictive analytics and advances in mechatronics have rendered the usage of Robotics to be far more pronounced, predominantly in areas of medical diagnostics, fault prediction in assembly line, manufacturing, hazardous situations and the like. It has opened up a new area of Cyber physical systems. Cyber Physical Systems are engineering systems that use Mechatronics and IoT, controlled by computer algorithm tightly integrated with Internet.
• Better Connectivity : Integration of smart sensors with IoT, diverse computer-computer ( machine to machine) data exchange protocols like P2P, HTTPS, QMMP, high capacity communication protocols of 5G, and tight cyber security models have rendered better, secure and large data connectivity across platforms like never before. IoT - continuously capture & analyze data, ascertain health of the machine tools, prevent down time, increase quality of yield etc. And data exchanges are secured to safeguard operations, prevent attacks, protect sensitive data, mitigate risks.

Challenges

Coupled with the promise that 1 4.0 offers, there are challenges as have been seen and reported in various contexts. These can be divided in following four categories;

Economic

High economic cost of implementation

Adoption of new business model

Integration of pre-existing systems (CAD,CAM, CAE,ERP,MES,PLM)

Ambiguous economic benefits

Social

Privacy concerns 

Surveillance and distrust

General reluctance to change 

Threat of redundancy of Corp IT projects

Loss of (low end) jobs 

Lack of required skills

Political

Lack of Regulations 

Unclear Legal issues

Lack of appetite to change

Organizational

Security of data 

Reliability & scalability 

Low management support 

Insufficient experience 

Integrity of Processes

Risk of investment paying back 

As a result, the risks perceived in the I 4.0 implementation are that the investments are needed ahead of well documented results in different types of industry project implementations, Skills are still far and few as there is a reported woeful shortage of experienced manpower, and jobs have to transform to next level of technological and managerial disciplines.

Cost – Benefits

While the debate continues and new business models get evolved out of the I 4.0 implementations, the predicted benefits ( as visualized) outweigh the costs. Below are some pointers in that direction. 

• According to Boston Consulting, the value created in I 4.0 implementation vast exceeds a single digit cost saving.
• According to IBM Watson, anticipate upto a 30 % increase in productivity as a result of I 4.0 implementation.
• In a report on manufacturing, fast intervention through early detection of faults and reduce waste. Even predict tool fatigue and the likely fault in a running assembly line.
• Optimization of assets to prevent underutilization through intelligent processing of real time data on asset movements, demand assessment and supply execution in pipelines.
• Benefits from security, scalability, data visibility, customer centricity, customization and innovation to meet specific needs in an industrial manufacturing or a supply chain operation.
• Opportunities offered beyond the goals of automation through implementation of new and adaptive business models.

Outlook - where do we go from here !

Industry 4.0 is a much talked about discipline. It has been fueled by the increasing automation in manufacturing, use of smart sensors and IoT devices to capture real time data from the field, larger play of technology of Artificial Intelligence and Machine learning for predictive analytics and decision support, enormity of data that is available to monetize using new emerging business models, availability of very high performance computing powers for meeting the processing speeds and complexity of the emerging data from an industrial operation. The implementation opportunities offered cover full cycle of industrial manufacturing, supply chain, services and organizational new business models that are directly relevant to the needs of the Society today.

As per the reports, currently only 30 % of manufacturing is expected to adopt I 4.0 and maximize benefits. The potential is huge, and is dictated by the extent and speed of adoption of the constituent technologies of I 4.0 mentioned in this Paper, and acceptance of the society of the principles on which 1 4.0 is based.

The terms Cyber Physical Systems, Smart Manufacturing, Factory of the Future, Industrial Internet etc have evolved as synonyms to I 4.0.

At the same time efforts, setting aside the often controversial argument of, if technology will make machine to replace Man or augment the Man, efforts need to focus on man and machine to reconcile and find ways and means to work together to realize the ultimate benefits of improved efficiency in operation, and demystify 1 4.0. This will lead to an increased interaction of human intelligence and cognitive computing. Eventually meet with the objective of serving humanity with improved efficiencies, better utilization of resources, cost savings, and clean environments.

Countries, notably USA, UK, Germany, France, Japan, China have programs that are implementing I 4.0 in Automobile manufacturing, Process industry, Supply –Chain. In India discrete I 4.0 implementations have been carried out in the Industry. Government is seized with the potential I 4.0 offers and is promoting policies and schemes to attract greater investments.

References : • The Factory of the Future (www.ibm.com/industrial/manufacturing) • Industry 4.0-Wikipedia(en.wikipedia.org/wiki/Industry_4.0 ) • Industry 4.0-Deloitte (www.deloitte.com/us/en/Insights/focus/Industry-4.0) • What is Industry 4.0 /The Industrial Internet of Things (www.Epicor.com/en-us/resource-centre) • Quick Guide to Industry 4.0 and 5.0 (www.I-scoop.en/Industry-4.o) • Architecture of Industry 4.0 based Manufacturing SystemsThesisCMU-RI-TR-16-43, July 2016 - Achal Arvind