Industry 4.0 Provides a Framework for Agile Manufacturing/ both Discrete and Process

Industry 4.0 is a relevant and significant shift in how industrial automation and operations management software is implemented and used to deliver significant business improvements.  However, it is too simplistic to directly apply the Industry 4.0 concepts to all manufacturing industries, or without considering industrial requirements which are not addressed by this activity.  The following is a set of viewpoints which are discussed in this white paper:

• Industry 4.0 is about the transformation from controlling focusing on process to “controlling the product/ order” and the “product/ order being self aware”.
• Industry 4.0 is about operations transformation, not about technology.
• Industry 4.0 provides a practical strategic framework for “lean” and “agile” industrial operations.
• Industry 4.0 addresses the needs of discrete and batch manufacturing, but it needs some adaptation for the heavy process and infrastructure industries.

Cloud computing and IT/OT convergence are often linked to implementing Industry 4.0, but these needs some adaptation to address “trustworthiness” of the architectures.  One emerging topic is Fog computing.

The functions and requirements of automation and operation management technology are even more relevant than before (contrary to some of the recent vendor claims).

Information standards such as IEC 61850/ISO9506, ISA-95/ISO62264, PRODML etc. are even more relevant than before .

Industry 4.0 is about the transformation from controlling focusing on process to “controlling the product/ order” and the “product/ order being self-aware”

Industry solutions and products have traditionally been focused on controlling the “process” in order to deliver the product.  But as the agility in the market changes, “new product introductions” and increasing, product lifetimes are shortening and becoming for individualized even to a point per order or customer.  This is driving the operational world towards “controlling the product/ Order” vs the process as the process will naturally be controlled if the equipment, process is set up for the order.  This requires the “order” to be “self-aware” of its required characteristics to satisfy the order/ customer.  So that it can make the system is set up/ and process runs according to the order. Driving “first run” success, and that the product/ order will create warnings, alarms, and enforce required actions to maintain it road to success.

Even in heavy process industries such as oil and gas, the requirement to develop more individualized products/ orders is key.  Scheduling is becoming a part of everyone’s role relative to their time slice/ span of awareness.

So the ability to track an order through the process, read and understand current condition of the product/ order, simulate the characteristics of the order, now and into the future based on the current condition and environment of the process, and equipment is a corner stone.

Industry 4.0 is about operations transformation

One of the central thoughts of this activity is transforming how work gets done.  Transformation of work often includes combinations of the following:

• When work gets done – proactive decision-making before desired changes and undesired conditions occur.  This is very different than “reacting better”.  This isn’t about “real time” work – it’s about “right time” work, which means early enough to make informed, accurate decisions, even no change.
• Where work gets done – local workers are essential, but an increasing use of traveling experts is essential.  These experts require standardized, trustworthy, and actionable information in order to add value.  Many experts spend more than 50% of their time in unplanned work and processing data to produce trustworthy “wisdom”.
• How work gets done – lean operations depends upon lean work; automation of information processing and distribution is essential.  The expert’s private spreadsheets are necessary for testing and innovation, but operations teams can only use and trust standardized, easily accessible and actionable information.
• Who does the work – a central thought in industrial operations is work simplification.  Fewer experts are available within the industrial enterprise, and in many locations around the world, younger technical workers refuse to live near the industrial facilities.  So much of the knowledge and wisdom must be embedded in the operations management architecture.

This transformation is essential; if there isn’t sufficient transformation, then Industry 4.0 is wasted.

Industry 4.0 is a practical strategic framework

One way of summarizing the central thoughts of this activity is that wasted work, cost, time and energy can be eliminated, and the product lifecycle can be optimized, by exploiting information about product design, manufacturing, distribution and use throughout the “supply chain”.  In order to exploit this information, much more data is necessary, and it must be transformed with appropriate context much earlier and to a much greater extent.  The enterprise which can constantly exploit this information has a sustainable competitive advantage.  This exploiting generates a terminology for the higher value information, such as the following:

• Data – raw values, automatically sensed and manually entered, including geographical/altitude location, time, and if possible, with asset identification (machine, material, vehicle etc.)
• Information – cleaned and reconciled data and derived information, such as efficiency and statistics
• Knowledge – information in context, including comparisons to targets and constraints, estimated times to thresholds, predicted failures
• Wisdom – optimal targets, prescriptive procedures to address desired and undesired situations

The above terminology is only one of several alternatives, but all of these address a foundational requirement that Industry 4.0 requires better information, not just more data.

Industry examples of transformation include:

Discrete and batch industries – accelerated “new product introduction”.  New products can be introduced earlier, manufacturability effort can be accelerated, and new learnings can be distributed across multiple manufacturing lines and facilities much faster.

Mining industry – higher “sales value of product”.  Exploiting the detailed knowledge of the metallurgy in each group of material in each location of the mines, the stockpiles, processing and transportation can significantly raise shipment prices and increase revenue.

Petroleum refining and petrochemicals industries – increased margins.  Exploiting the detailed knowledge of the chemistry of the fluids and the capabilities of the processing equipment can significantly reduce the cost of raw material purchases and processing costs for the same output.

Power generation and transmission industries – exploiting the detailed knowledge of current and upcoming power demand, and knowledge about current and upcoming capabilities of generation and transmission can significantly increase reliability, increase revenue and reduce emissions.

Cyber Physical and Operational Management Evolution

In recent months Stan DeVries and I as part of Common Architecture Team, and also investigating large opportunities have spent many hours discussing the internet of things, Industrie 4.0, and shift to Cyber Physical architectures. It is fundamental for the rapid innovation businesses will need in order to stay competitive, both delivering products, but evolving efficiency and leveraging an effective "operational team", Stan submitted this blog on the subject.

Recently the academic phrase “cyber-physical systems” has appeared in presentations and articles on smart manufacturing and Industry 4.0.  Much of the emphasis has been on the “cyber” element, with frequent example of automation.  This may imply “lights out” operations, which might be achievable and desirable in some operations, but unnecessary, in-feasible and undesirable in most.  It should be helpful to consider one of the models of cyber-physical systems, which is called the Boyd OODA Loop, as shown in the following diagram:

Colonel Boyd was an excellent fighter pilot and military strategist.  The key elements of his decision model are:

• Observation: the collection of data by means of the senses
• Orientation: the analysis and synthesis of data to form one's current mental perspective
• Decision: the determination of a course of action based on one's current mental perspective
• Action: the physical playing-out of decisions

Using this model, automation improves the Observation and Orientation so that users engage with only the “right” information, at the “right” time (often earlier than real-time) in the”right” context – for the “right” results.

While the Boyd decision model is excellent for one or a few workers, another model is necessary for considering an entire operation, such as a manufacturing plant, a power generation station, petroleum refinery, oilfield etc.

If we accept that the main value of the automation is to improve the Observation and Orientation, then the above diagram implements these 2 important steps in what can be called the Smart Solution Center, which is a combination of a technology/data center and specialists who are providing support, improvement and instruction to other workers.  One of the key outputs of the Smart Solution Center, so that most of the work performed by knowledge workers within that Center and other workers spend the majority of their time on planned work, instead of being consumed with reactive work.

But automation of Observation and Orientation must be extremely accurate and trustworthy.  To achieve and sustain these attributes, we recommend a “Virtual Smart Plant” which is used to design, modify, test and train workers.  This is also key to sustaining behavior change and if possible, culture change.  Best practices have shown that workers change their performance in lasting ways if they experience the change for themselves, and especially if they can experience new learning in a “safe” environment.

In the above diagram, the “work orders” are more than task lists, but a combination of recipes, KPI targets, instructions, handover/turnover actions etc.  The black rectangle at the center bottom of the diagram is focused on people, who are doing what humans do best: dealing with new knowledge, managing complexity, and navigating change.

So the key to applying “cyber-physical systems” is optimizing the use of the workers, not eliminating them, and this optimization requires using technology in a “smart” manner, such as focusing on Observation and Orientation.

An increasing amount of leading companies are developing the "Smart Solution Centers" (often reference to as Centers of Excellence) where they can physical one location or a "virtual smart center" maximizing the leverage of key thought leaders in the analysis and development of operational/ process innovations. A good example of this is Rio Tinto's Process Excellence Center for mining in Brisbane (plenty of write up on this) where data is analysed converted into effective knowledge through simulation, analysis models, to improve operational running of mine process. 

  

Smart XXXX: What does it mean!!!

So often today you hear the word “smart” put on the front of a segment describing the transformational program encompassing many of the Internet of Things concepts.

Smart Cities, Smart Farms/ Agriculture, Smart Airports, Smart Plants, Smart Fields etc.

Are they different or do they all come down to a basic set of concepts, transformations that are applied to that industry to significantly shift the needle in operational efficiency?

 Fair question, and so often lately I am being asked what is the difference between IT/OT, IOT, and Smart xxx? So I thought it was worth a discussion, as I suspect there different interactions.

To me the discussion of “smart/intelligent” industrial it is all about achieving “operational Optimization/ Excellence”, to suite the required production at the most effective time, cost. This is a shift from time based production and managing the process to managing the production of product/service. Driving the optimized execution of work / actions on operational processes for that product/service delivery.

At the core it is about changing the way in which we manage and execute work tasks, either automated or actions with human intervention so that only required work is performed at the correct time.  

“Smart Strategies” are fundamentally different from current IoT, Big Data etc. thinking:

• The IoT, Big Data etc. Initiatives/trends can be characterized as offering the 5 “any’s” – any information, in any context, at any time, to any user, for any action
• “Smart” products and operations can be characterized as offering the 5 “right’s” – the right information, in the right context (operations situation), at the right time (which is often earlier than “real-time”), to the right users for the right actions (which are often preventative and at best prescriptive).

All fundamental on the journey towards “operational excellence.”

That said “Smart Strategies” will employ the services of IOT, and big data, but the key is “Smart” is about tightening the execution of an operation process relative to the current product delivery expectations. A key concept is that the Operational Process, (no matter if it is in a city, airport, or production line) understands:

•        What it is expected to deliver in characteristics of product or service, and when
•        It is “self-aware” of it’s condition and ability to deliver that product/ service, due to capability, materials and the situation it is in.
•        It is able to then request and interact with other process, applications, assets and people to gain the required actions needed to succeed and when. 

This is a transformation from just understanding it is taking control of the process, as opposed to time schedule actions.

Time for Information Driven Manufacturing!

Information Driven Manufacturing concept is starting gain traction in the thought leaders. Information Driven Manufacturing is a manufacturing strategy that combines the concepts of collaboration and value network manufacturing, building on the newer technologies to achieve and sustain a agile competitive multi plant business. A key concept to this strategy is that explicitly recognizes that avoiding change, while comfortable, may represent a bigger risk for the organization that the risk associated with introducing new solutions where appropriate.  There is a different culture not taking technology for the sake of it, but an attitude that understands the need for alignment of people, value asset network (multi-plants) and business and operational processes, to reduce cost, but most of all provide a flexible manufacturing base that can adjust with market providing the necessary agility to absorb market change, acquisitions, and new products rapidly and in a cost effective manner.

 

 

Source ARC Feb 2013

Information Driven manufacturers take a holistic view of manufacturing and the production plant’s role within the extended value network. They apply information technology broadly  to improve or replace business process. With the maturity of internet, workflow, databases, and other technologies there is a host of possibilities that can be applied in a program to improve the dynamic nature of the whole manufacturing from people to assets, and processes, to enable consistency of execution and therefore the opportunity to be dynamic to absorb, evolve to change.

The cornerstone of  information driven company is the empowerment of all people in their roles, to make decisions and act as an aligned team, based upon process and business information, provided in a holistic view (across assets E.g.| unified model despite the underlying sources), contextualized, visualized so that it can be analyzed easily relative to their roles. Key is making sure this information and core data are a “Trusted system” and the leading companies are now applying consistent embedded actions to go with the information decision so that consistency in action, and reduction in skill experience are needed to achieve a consistent, timely result.

The culture in an information driven manufacturing company, is understood the value and need of change/ evolution in a constructive way, but executing this change on proven technologies but not just used in their business, but looking outside their business and asking “why cannot we apply that for this____”. They have active investigations through internal, and external looking at:

 

More and more I am engaging with leading companies who are looking at open minded people to make a team who can constructively develop a value program. It is important to recognize this is more than one program, it is alignment of programs, technologies and cultural journey which leading companies are on, and potential benefits are significant in agility (market share) and long term cost, through staying 'ever green" and aligned.