Reduction technical skilled capacity at site, accessing new sites, equipment with limited technical skills “calls for the Industrial Internet of Things”

For the past couple of weeks I have been engaged in opportunities / projects from Coal Seam Gas fields where the expectation is to plug in a well, and the system must self-discover and set up, to farms where the fields are being monitored, the solos and storage vessels being monitors, to cattle waring health senses. With many other applications in between, but all came with two major requirements:

1/ No dependency on technical skilled people on site or close to site, so the system must be plug and play, at a commodity “throw away” price.

2/ Transparency to operational information, and asset health awareness across the value chain, (more than often across different legal companies contributing to product value).

The Industrial Internet of Things, provides the opportunity, as long as it thought through, not just thrown out there. Considerations on:

• Cost and sustainability of devices e.g. the tendency is to go for throw away but with that comes the need to characterize the devices for the situation
• How do you configure and set up the devices with no skill on site, but do it in a sustainable way
• How do you manage 1000s of devices so they are operationally coordinated?
• How do you understand health and availability of devices so you can take action to maintain operational continuity
• That is before you get to the data / information getting to a location that can leverage it.

But this is classic Industrial Internet of Things where we are seeing tiny, simple devices with connectivity, but with a processor with Linux operating system which we can down load and engine provide character for the role, at a cost of less $50, often less $20. No site skill needed to “plug and Play” and enable the device now the opportunities are coming real and immense.

I found this diagram summed up the opportunity and obstacles well:

What hit me was the two obstacle of:

• ·         Insufficient skills of technology staff.
• ·         Use of Legacy Systems

But the IIOT must resolve these by providing edge devices that do not need technical skills on site, and can connect and enable legacy equipment to integrate. But the IIOT service fabric must provide the expertise and capability to remotely enable devices with the required character.

The more and more I look places that where not enabled at all, transforming to agile efficient business through IIOT being applied in Industrie 4.0 logic.

Perfect example was this week when I visit a person who had 2 dairy farms that he has to transform the value he is delivering beyond just milk to the service he can deliver and good “gate margin”. He has now got his paddocks with moisture senses in them using devices that last 10 years and cost less than $10 to connect a year, to trucks, and vehicles all being monitored. All the cows are being wired up for health awareness, and the milk capture and processing is being monitored. But he does not have a PC on plant, all the data goes to the cloud and he can have eyes for decisions across the two dairies as if they were one. He had a strategy to align two properties look for the “edge” but now you have typical location that was not automated now Information driven. But not with more people, and the cost in opex so he can budget it into his “gate Margin”.

But he has a strategy and took and an opportunity, which he is still on journey. The fact that only 25% of companies in the above survey had an IIOT is indicative of the market not really understanding the opportunity, which will become a requirement to survive in the future. The key is it is not about IIOT it is just one of the enablers, it is the requirement to become “hyper agile” in a dynamic world.   

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.