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.
‘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.
