Foundation for Industry 4.0

IIndustry 4.0 (source Wikipedia)  is a name given to the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things, cloud computing^[and cognitive computing. Industry 4.0 is commonly referred to as the fourth industrial revolution.

Industry 4.0 fosters what has been called a "smart factory". Within modular structured smart factories, cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralized decisions. Over the Internet of Things, cyber-physical systems communicate and cooperate with each other and with humans in real-time both internally and across organizational services offered and used by participants of the value chain.

Industry 4.0 is a collective term for technologies and concepts of value chain organization. Based on the technological concepts of cyber-physical systems, the Internet of Things and the Internet of Services, it facilitates the vision of the Smart Factory. Within the modular structured Smart Factories of Industry 4.0. Industry 4.0 operates within this framework:

·         Cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralized decisions

·         Over the Internet of Things, Cyber-physical systems communicate and cooperate with each other and humans in real time

·         Via the Internet of Services, both internal and cross-organizational services are offered and utilized by participants of the value chain.

Industry 4.0 is based on six design principles. These principles support companies in identifying and implementing Industry 4.0 scenarios.

• Interoperability: the ability of cyber-physical systems (i.e. workpiece carriers, assembly stations and products), humans and Smart Factories to connect and communicate with each other via the Internet of Things and the Internet of Services
• Virtualization: a virtual copy of the Smart Factory which is created by linking sensor data (from monitoring physical processes) with virtual plant models and simulation models
• Decentralization: the ability of cyber-physical systems within Smart Factories to make decisions on their own. Decentralized decisions: The ability of cyber physical systems to make decisions on their own and to perform their tasks as autonomously as possible. Only in the case of exceptions, interferences, or conflicting goals, are tasks delegated to a higher level.
• Real-Time Capability: the capability to collect and analyze data and provide the insights immediately
• Service Orientation: offering of services (of cyber-physical systems, humans and Smart Factories) via the Internet of Services. Technical assistance:  The ability of assistance systems to support humans by aggregating and visualizing information comprehensively for making informed decisions and solving urgent problems on short notice. Second, the ability of cyber physical systems to physically support humans by conducting a range of tasks that are unpleasant, too exhausting, or unsafe for their human co-workers.
• Modularity: flexible adaptation of Smart Factories for changing requirements of individual modules
• Information transparency: The transparency afforded by Industry 4.0 technology provides operators with vast amounts of useful information needed to make appropriate decisions. Inter-connectivity allows operators to collect immense amounts of data and information from all points in the manufacturing process, thus aiding functionality and identifying key areas that can benefit from innovation and improvement. Information that is required by the sub-system within digital architecture.

There is a danger that that Industry 4.0 will just be another failure and big hype whereby significant investment fail to move it from trial and pilots into realization.

Forbers: Why Industrial IOT Is Usually A Failure - And How To Fix It

‘In mid-2017, Cisco produced a report of survey results indicating that companies considered 76% of their IOT initiatives failures, and a majority said that IOT initiatives looked good on paper, but turned out to be more complex than expected’

Reality is that most organization have failed to achieve efficacy in Industry 3.0 . 

Industry 3.0

Industry 3.0, 4.0 to +++(adaption of Machine Learning and Artificial Intelligence)  will still have to comply to key Supply Chain Process which are plan , make and deliver effectively and efficiently by maximizing system potential (constraints), minimize waste , quality product and on time delivery.

Most organization do not have an integrated system view cockpit/dashboard to provide linked metrics. Overall equipment effectives (OEE) is of little value on its own without correlation to inventory levels and backorder. High OEE correlating with rising inventory and backorder indicates poor effectiveness.

Traditional governance frameworks are compartmentalized rather than system wide framework that is able to deal with system level of disorder: from complex system to complicated to chaotic.

To ensure Industry 4.0 realization benefits the following solid foundation needs to be put in place:

       

•      Governance framework (based on Viable System Model) that can deal with complexity and better equipped to respond to signals from internet of services. This governance framework will enable effective use of input that flows from Industry 4.0 framework and ensures correct decision (do the right things)

 Industry 4.0 cybernetic Approach

•          Dashboard/Cockpit that shows correlated metrics and associated events to enable better decision making and next best actions
•          Getting Industry 3.0 working efficiently and effectively with the necessary subsystems (ERP ) device connectivity, lean manufacturing

Note: Governance framework and the cockpit is not only fundamental to Industry 4.0 but also critical to ensure viability, sustainability and adaptation: doing the right thing in terms of dealing with system complexity, maximizing system potential, viability, and sustainability.  

The performance of the system depends on how well the parts fit together, not how well they perform individually and the ‘whole’ system exhibits emergent properties that are not to be found in its parts.

Potentiality: This is what the system should be doing within the boundaries of existing system state (same function, structure, identity, and feedback’s) by developing its existing resources  and removing constraints or elevating constraints to maximize throughput, improvements to  management control and processes although still operating within the bounds of what is already known to be feasible.

A constraint is a limitation, imposed by outside circumstances or by system behavior (ourselves) , that materially affects our ability to do something and limits a person or an organization in achieving their goal. Constraints directly impact systemic capability and potentiality.

There is a subtle difference between a constraint and a bottleneck.

A bottleneck (resource) is a resource with capacity less or equal to demand while a constraint is a limiting factor to organization’s performance, an obstacle to the organization achieving its goal.

Wikipedia:  Cyber Physical Systems (CPS)

A cyber-physical (also styled cyber physical) system (CPS) is a mechanism that is controlled or monitored by computer-based algorithms, tightly integrated with the Internet and its users. In cyber-physical systems, physical and software components are deeply intertwined, each operating on different spatial and temporal scales, exhibiting multiple and distinct behavioral modalities, and interacting with each other in a lot of ways that change with context. Examples of CPS include smart grid, autonomous automobile systems, medical monitoring, process control systems, robotics systems, and automatic pilot avionics.

CPS involves transdisciplinary approaches, merging theory of cybernetics, mechatronics, design and process science. The process control is often referred to as embedded systems. In embedded systems, the emphasis tends to be more on the computational elements, and less on an intense link between the computational and physical elements. CPS is also similar to the Internet of Things (IoT), sharing the same basic architecture; nevertheless, CPS presents a higher combination and coordination between physical and computational elements.

About Viable System Model

The viable system model (VSM) is a model of the organisational structure of any autonomous system capable of producing itself. A viable system is any system organised in such a way as to meet the demands of surviving in the changing environment. One of the prime features of systems that survive is that they are adaptable. The VSM expresses a model for a viable system, which is an abstracted cybernetic (regulation theory) description that is claimed to be applicable to any organisation that is a viable system and capable of autonomy.