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.

Industrial Ethernet/ “Internet of Things” Is it About putting Data in the Cloud? Or Interactivity?

Sorry for missing last week, time seems short when on the road with short flights.

As I fly the final leg home after a month on the road many brainstorming multi day workshops around different strategic thinking, but without a doubt the “Internet of Things’ applied in industrial/ manufacturing space brought up many ideas and many questions.

Certainly the discussion of “Cloud” vs “Internet of things” is it about getting to data from all types of devices and making that more available? Certainly that is one case, but certainly it is not a compelling case.

The “Internet of things” is about self-configuring devices, these could instruments, motors trucks, and mobile devices, fixed and roaming devices. Too many of you the IOT definition I believed was clear, but the workshops showed the confusion between taking and existing industrial application to the “Cloud” connecting through safe but tradition device integration paradigms, vs an interactive “self-configuring” environment of devices and systems, that is a new device integration, management paradigm.

Also, it is important to note it is not just about gathering data from devices to the cloud, and exposing it, the real opportunity comes in the interaction between devices, that the environment make the devices “self-aware” and able to interact. A natural example is that mobile devices of a roaming user is interacting with the other devices in the immediate area. Enabling interacting, and constant awareness and warnings of the current environment state, relative to a stability, and safety. Combine this with ever increasing transformation to managing Operational work vs monitoring, where the “work” or “activity” includes the information, action in the context of “activity”.

The fact that a device is now “self-configuring”, so you can from an IOT system “discover” the devices out there and configure the co-ordination system in the cloud, making other systems aware of them. This is a clear case for segments that are physically distributed such as cities, airports, upstream gas fields, mining, pipelines etc. Where the cost of aligning the devices has been too expensive, now with wireless but even more 4G networks like we seeing in the remote “Pilbara” region on Western Australia, the opportunity for plug and play devices that are “edge/ GPRS” enabled, and IOT enabled can be discovered, configured and aligned. As devices are swapped in and out no matter site the size, the configuration moves from an instrumentation job to anyone. This frictionless experience is key in configuration/ and sustaining. The increased speed of systems, decisions and agility required drives up complexity of systems, but this cannot drive up lifecycle cost, and this can only go away through Self Configuration, enablement of anyone to enable the system to run, this become clear as the key requirement of the IOT.

The chart below shows the expected industry segments to adopt, many are well engaged.

But why is there a slow take up, mainly I believe to unawareness, lack of understanding, and readiness? But this is changing, the IOT platforms are coming on to the market that will drive down the cost of achieving IOT, but it will still be a journey. The diagram below shows from one of the workshops the key challenges in adoption, I expect these to fall away fast over the next 2 to 3 years. I cannot see how we going achieve the agility, with the dynamic market, operational workforce at a sustainable cost that is reasonable without this paradigm shift, to IOT as interactive landscape. In the many sessions I held with end users, engineers and people across the company and industry, the real initial opportunity is not in the big plants it is in the “collaborative Industrial Landscape” of small plants and assets aligning with people and processes.

 Certainly the interest, like cloud is growing, and the infrastructure is maturing that this will be reality in helping to addressing the modern industrial landscape challengers in a very different landscape than we had in 90s, 2000s, and 2010s, I will discuss more on this fundamental event next week.

Momentum grows on Internet of Things in Industrial and Manufacturing Environment

As I enter another week of brainstorming workshops across Schneider Software, with thought leaders, we are working through innovations on technology, architecture and process. Centered around the “cloud” and “Internet of things” while we have offerings happening in both areas, we need shift from offerings to these technologies be a natural part of the industrial architecture and process of buying and applying an industrial solution. I also spoke with many people over the last 2 weeks across the world not about technology but about the solution challengers and it was clear that the three main challengers kept coming up:

•  People and operational change of moving to teams which involved remote workers and virtual experts
•  Agility to change production, and process quickly and efficiently
•  Holistic control across the manufacturing industrial assets. This required the expansion to   assets that could be mobile or remote to traditional industrial plant, yet still are apart of Value Chain that they are accountable.

Accountability came up over and over again; this means different things from a safety of people to food safety so trace ability etc to efficiency and responsibility to the environment and impact. It was clear in all the discussions that a change in thinking of architecture and approach was needed but instead of its being a “dream” it is really possible today in a sustainable way using such technologies as Cloud and Internet of Things. The architecture below is an example of distributed, but needing a unified operational experience across roles across devices, and unifying devices.

Also during the week I came across two articles one from Microsoft and another from ARC on Hanover fair both supporting the increased momentum in the market for Internet of Things.

Key as MS  points out below the opportunity to investigate and improve your business by naturally looking beyond the traditional architectures, overcoming the concerns such as security, by implementing secure architectures and approaches “that does not mean isolation”.   

The Operational Transformation is here from a design point of view, again this is one of the technologies and approaches to be employed to achieve the operational workspace and efficiency required in the flat world.