Final Post: The Journey of Data Transformation to Wisdom to Enable Smart Work

This post will be my final one in this blog, as forum does not seem to be working as it once did, and we exploring new approaches to getting thought leadership out.
Thank you for your interest if you feel like we should continue in some form, please post a comment.

This final post I will post a paper Stan DeVries and I have just completed that summaries the journey, and pitfalls on that path we see leading companies following to achieve Operational Excellence.

In today’s “flat world” of demand-driven supply, the need for agility is only going to move faster in the next 10 years.  This is driving leading companies to transform their operational landscape in systems, assets and culture in a shift to “smart work.”  Agility transforms their thinking from a process-centric to a product and production focus, which requires a dynamic, agile work environment between assets/machines, applications and people.  Aligned decisions and actions across a multi-site product value/supply chain is crucial, and  requires the ongoing push of a combination of automated (embedded) wisdom and augmented Intelligence (human wisdom).

The paradigm shift from the traditional “lights out manufacturing concept” of fully automated systems  in an agile world  shifting to scheduled work that can be dynamically planned requires both:

• Automated embedded Intelligence and knowledge
• Augmented Intelligence using humans to address dynamic change

Foundational to this shift is an environment where a worker can have the mind space to understand the larger changing situation and make augmented intelligent decisions and actions.  To provide this, data is transformed naturally into operationalized information upon which decisions can made, then extended to be combined with “tacit, applied knowledge;” it can provide incredible value when taking operational actions.

The explosion of information across industrial operations and enterprises creates a new challenge – how to find the “needles” of wisdom in the enormous “haystack” of information.

One of the analogies for the value and type of information is a chain from “data” through “information” and “knowledge” to “wisdom.”  In the industrial manufacturing and processing context, it may be helpful to use the following definitions:

• Data  – raw data, which varies in quality, structure, naming, type and format
• Information  – enhanced data, which has better quality and asset structure, and may have more useable naming, types and formats
• Knowledge  – information with useful operational context, such as proximity to targets and limits, batch records, historical and forecasted trends, alarm states, estimated useful life, efficiency etc.
• Wisdom  – prescriptive advice and procedures to help achieve targets such as safety, health, environment, quality, schedule, throughput, efficiency, yields, profits etc.

An example of this transformation: imagine driving along a freeway in California which you do not know.  You rent a car with a GPS.  

• Data: the GPS knows that I am on a freeway, at 80 mph.
• Information: it is “situationally aware” that I am heading south, on the I-405 freeway
• Knowledge: it works with other services to determine that 10 miles ahead the traffic is stopped, and provides me with a warning that I will be delayed due to a traffic hazard. It has combined traffic knowledge with my location, speed, and destination to provide timely, advanced decision support knowledge that I can use to potentially take an action.
• Wisdom: the GPS provides two alternative routes on the display giving me time and characteristics of the two alternatives. Without me having to take my eyes of road and use an A-Z directory, I have been:
• warned ahead of time of a potential issue in achieving my destination on time
• given two actions at my fingertips based upon route characteristics I desire, to guide me through a neighborhood and route I have never been on.

There is no reason why this same journey of data transformation to wisdom cannot apply to manufacturing operations.

Avoiding the Pitfalls Going to Wisdom

Many companies stand on the edge of a data swamp that is growing quickly, with the Industrial Internet of Things and Smart Manufacturing providing access to an exponential level of additional data from their industrial value chain.  This data influx can either “bog them down” on growth, or if leveraged to achieve proportional growth in “knowledge and wisdom” could propel a new level of operational agility.  The Fourth Industrial Revolution (Industrie 4.0) provides a potential framework for leading this ubiquitous transformation.  Major industrial organizations are now realizing the incredible value that can be extracted from data and are applying the time, resources and new technologies such as big data and machine learning, combined with a new evolution in operational culture to leverage this potential.

Those operating in manufacturing have been living for decades with vast amounts of data located in historians, equipment logs and across their extended supply chain network. Data, in and of itself, is not of much value.  The same can be said for reams of paperwork that document best practices-- it isn’t of much value sitting on a desk or in a document management system.

The same discussion could be used for companies running on paper-based operations and paper “black book” operations (as one operations department mentioned), where the knowledge and wisdom to take correct actions based upon experience or “instinct” also becomes an unsustainable model.

The diagram below shows the quadrants of potential situations where companies can find themselves with “experience vs data.”  Today, many companies find themselves on one of two ends of the spectrum of knowledge and data, and both ends leave companies in a state of limited agility to change to required speeds.

Summary

Manufacturing is in a constant drive to improve performance, and transformation of work has become the main method to achieve and sustain this.  Higher capacity or more efficient machinery and processes aren’t sufficient any more.  Manufacturers with agile and cyclical operations need a method to remain cost competitive during the lower throughput periods, yet remain responsive enough to take full advantage of high throughput or high margin conditions.

Implementing systems which transform work using higher value information and reliability change when, where  and/or how users make decisions, and is the foundation for this next level of improvement.

Operational Transformation through Smart Work is a journey, and technology is only one of the key elements.  The user culture must adapt, similar to the previous waves of quality, safety, health and environmental improvements.  The journey advances with work process improvements, as applied to sections of a site or an entire site.  Existing software must be assessed in terms of delivering knowledge and wisdom, supporting mobile and traveling workers, with the goal of significantly reducing the skill and effort to maintain them.  The journey is worthwhile, practical and essential for manufacturers not only to stay competitive, but thrive.  

A Culture of Empowerment: Problem Solving at Source

 As we observe the world around us change, and more and more the focus shifts to a “new way to operationally work”, we see leading thought companies start introducing innovations in their culture.

One of these we now seen in two leading manufacturing companies who are shifting to the “New World of Work” and introducing not just technology but key cultural changes. One of these is the “Empowerment Culture” one of the strategies these companies is shifting the problem solving to the source.

This overcomes the delays in decisions through having decisions go up the tree by increasing the skill of the workers closer to action, and empowering them to be able to make decisions. This means skill development, embedding knowledge and experience in the system to help facilitate the correct timely decision.

The diagram below shows the structure

This allows the different levels, roles, and time horizons to focus on their problem solving optimizing the overall operational agility.

The “edge” worker on the front line is performing situational problem solving relative to production and asset at the NOW.

The plant supervisor have a wider time horizon of hours, and is looking at the plan, and adjusting thru “Systemic” thinking.

While management is then left with the bigger picture of strategic thinking, and problem solving, setting the overall direction.

Now if all decisions came to management they would be ‘firefighting” not free to think strategically and often the decisions would be delayed effecting production, efficiency and safety.

Getting out from behind the desk/ control terminal requires aligned work

The above comment was made to me by an oil and gas company, and when I enquired to their expectation, it was clear that they wanted to empower "controllers" (operators) to be responsible for more. Enable decisions to be made faster while also gaining consistency across teams and shifts.

Transforming the traditional role of sitting in a control room behind a terminal, to a dynamic role, where the operator can get up and roam to investigate, make decisions and take actions in a timelier manner. This concept embraces all of the concepts this blog has raised over the last couple of months and shows the transition in the industrial sector to focusing operational empowerment.  

By unleashing the controller from their seat, they are free to investigate, see for themselves, and interact with others with experience to make informed decisions faster.

What is the reason why users have been locked to the desk/ control room, why has this transition not happened successfully before?

It is simple, the requirement to be monitoring the plant. A traditional control room is the central place alarms, notifications were traditionally piped.

So to free up the user, to leave the control room, the user needs to empowered with situational plant awareness, freed from monitoring, shifting to the experience of exception based notification. As the user roams the plant, the user is still responsible, and aware, and able to make decisions across the plant he is responsible for even if he not in view of that a particular piece of equipment. Driving the requirement for the mobile device the user carries to allow notification, drill thru access to information and ability to collaborate so the dependency to sit in the control room has lifted.

The second key part of the transformation/ enablement of a edge worker is that their work, tasks and associated materials can transfer with them. As the world moves to planned work, a user may start work task on a PC in the control room, but now move out to execute close action. As the user goes through the different steps, the associated material and actions are at his finders tips. The operational work can be generated , assigned and re directed from all terminal.s and devices.

So freeing up people is not just about providing mobile data taking the HMI Mobile. It requires the transformation to task based integrated operational environment where the "edge worker" is free to move.

System will notify him of situations, and he can take action, whilst also providing him with the opportunity to execute tasks. The information must free them to navigate with freedom, no matter the format, no matter where they start an activity, and have access to everything.   Why now? The technology is here with wireless plants, commodity devices to suite different applications/ roles, and the desire and culture to enable the flexible team, and design to enable exception based notification. The information, to knowledge systems are here to enable navigation through the required information while his situation changes. No longer are clients specific applications, they are role and situational based.

For all situations, freeing the anchors that hold people to the desk, and enable the reality of a flexible , empowered edge team. 

  

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.

Regulation Drives Companies to “Paperless” system, but they Need to Integrated

Regulation is a growing principle required in solutions. The growing demand is coming from increased government regulations on industry around environmental impact, or trace-ability, really driving “Accountability” for actions and being able to determine history fast. Not all the drive is coming from government regulation requirements, in many industries it is being driven by the consumer as a value differentiator for the products.

So we are seeing investments in serialization systems in Life Science and Food and Bev, which extend the existing packaging lines, and are integrated to MES and ERP systems.

But the area that is interesting to me is not this section it is the implementation of “paperless strategies” removing the “clipboard” and replacing it with some forms based software. I have reviewed 3 of these systems, that are driving consistency in capturing of information. Within built rules that drive the user to capture the required points, take the required actions in order to satisfy the particular regulation or combination of regulations required for shipping that product.

While the shift to “paperless” has been a goal for a long while and people have headed down this when implementing a MES (Manufacturing Execution System), this is logical as the drive to paper less in integrated to operational events and practices. Providing an end to end trace-ability, and view into the manufacturing history of the solution.  

What concerns me what I started to see in Oil and Gas, Mining, F & B is these isolated event/ forms capturing systems that are put in isolated from the production/ operations system. Yes they may have some events and points integrated but the procedures are not an extension of the operational system. The captured data is in isolation of from operational/ production data, it should be captured along with the production records of what materials were consumed, who was operating the machine, and what product was going thru the system.

We seeing in the integrated solutions, the tradition operational/ mes system, being extended with a Business Process Modeling system, introducing workflows that can be configured to be triggered from the real time operational systems at Scada/ DCS or at the operational levels. Driving the capture, check, validation of process data boundary violation, or required capture to align with “inspection requirements “ from the ERP. The workflows natively interact between the systems, just extending the process operational processes but provide forms to drive intuitive actions, and capture. 

The most important part is that these are extendable and customization so that your companies capabilities, uniqueness can be captured as “best practices”. Most of all these are not separate systems they native extensions of the MES/ Supervisory automation, Quality applications driving the results and information back into the consistent repository.

So as you look going paperless, avoid doing it in isolation of the other systems, it must be extension, so that the operational process and practices from execution, to quality process, and process management, and extended with regulation requirement in a native way both from an operational experience process as well as data / information integration.

ISA-95 “Vertical” and “Horizontal” Integration

ISA-95 is an international standard which has been used for 20 years; recent transformations in operations management and computing technology has caused some to question its importance.

ISA-95 has now become extremely important – it is necessary to understand what this standard does before we can understand its importance.  This standard is an “information exchange model” focused on “level 3” (operations management functions), with specifications for information exchanges between level 4 (enterprise software) and level 3, and level 3 to level 3.

Before 2010, many operations management implementations were relatively simple, using what the author calls “vertical” integration – the dominant pattern was exchanges between level 3 and level 4, such as the following example:

In recent years, more industrial facilities have adopted the use of operations management software, including many more software components, and more customer industries, such as petroleum refining, mining etc.  For many implementations, the dominant pattern is exchanges between level 3, such as the following example:

In the above diagram, several of these activities are often implemented with multiple applications, such as work management, electronic logbook, laboratory information management, material movement tracking, data reconciliation etc. – some implementations have more than 20 applications for a single site, with multiple sites (a few dozen in a large petroleum company, several hundred in a large food and beverage company).  Much of the information exchange is level 3 to level 3 or what the author calls “vertical” integration.

So, why has ISA-95 become very important now?  One of the main reasons is that information is exchanged 10-100 times more frequently, with 10-100 times more detail.  Materials have sub materials – even mining, petroleum refining and petrochemicals deal with molecules or groups of like molecules.  Lots have sub-lots; work has much greater detail.  Determining the suitability of a previously trusted software application (including the ubiquitous Excel files) for this information exchange becomes easier when assessed against this standard.

ISA-95 and Operations Transformation "How is the Cloud Entering S95 models"

The ISA-95 standard has been in place for over 20 years, and recent progress in operations management transformation and Cloud adoption have triggered questions about this standard.  The author offers an observation:

•        ISA-95 is also essential for radical technology transformation using Cloud.

Currently, there is a lot of hype and misinformation about Cloud, especially for industrial operations.  3 patterns appear from this marketing activity:

How can architecture decisions be made?  Consider the following information model in light of the 3 implementation options summarized above:

Wherever these functions are implemented in different locations (with or without Cloud), what mechanisms are necessary for requirements such as “business continuity”, “access control” etc.?  How much context must be exchanged between sites and the Cloud to recover from network and Cloud outages?  Only an appropriately detailed and standardized information model can help.

ISA-95 focuses on the functions of operations management; it is independent of the implementation, including technology and location.  It is the foundation for designing, implementing and evolving architectures for operations management transformation, especially when Cloud is adopted.

ISA-95 and Operations Transformation

Tyhe questions around S95 where and how to use continue to grow, especially as the guidance for operational system alignment, we though it was time to give an update.

The ISA-95 standard has been in place for over 20 years, and recent progress in operations management transformation and Cloud adoption have triggered questions about this standard.  The author offers an observation:

·         ISA-95 is essential for higher performing operations who are implementing sustainable improvements, in conjunction with best practices such as lean.

Higher performing operations often have the capability to achieve and sustain best practices which directly produce best business performance.  A key enabler to this improvement is exchanging operations knowledge in more detail and more frequently.  Examples include:

•          Tracking of containers in high-volume continuous food cooking, so that successfully cooked containers can be recovered after a machinery failure with compliant tracking and reporting.
•          Assessment and tracking of ore grades in mining from the pit to the port, including in the stock piles and in the rail cars, so that yields and prices can be optimized.
•          Assessment and tracking of chemical components in petroleum refining and petrochemical manufacturing, so that yields and costs can be optimized.
•          Detailed and accelerated distribution of new manufacturing instruction in consumer-packaged goods, food and beverage and discrete/aerospace manufacturing, so that new products can be introduced much faster.

Each of the above examples depend upon exchanging “insight” in great detail throughout the manufacturing/processing and its associated supply chain.  Lean principles can be reliably applied, including eliminating wasted work; specialists can reduce time spent on producing useful information and focus on continuous improvement.

ISA-95 provides an information exchange model, and standardizes how activities are defined and relate to each other, such as quality, inventory, maintenance, production and the notion of “work”.  Sets of information are exchanged as “events”, and the relationships between activities and events are standardized.  Without this information exchange model, knowledge workers don’t have a sustainable operations management system, and as a result, the organization doesn’t have sufficiently useful information.

How can architecture decisions be made?  Consider the following information model in light of the 3 implementation options summarized above:

Wherever these functions are implemented in different locations (with or without Cloud), what mechanisms are necessary for requirements such as “business continuity”, “access control” etc.?  How much context must be exchanged between sites and the Cloud to recover from network and Cloud outages?  Only an appropriately detailed and standardized information model can help.

ISA-95 focuses on the functions of operations management; it is independent of the implementation, including technology and location.  It is the foundation of high performance operations management transformation.

Operations Innovation & Transformation – Flexible Teams

The 4 quadrants described in the article “Operations Innovation & Transformation – the 4 Types” positions the lower right quadrant as a strategy for using a team of human assets in a new way.

In this quadrant, teams of specialists (with the same or different areas of specialization) are grouped to provide value improvement to a group of physical assets, and the group of physical assets can be used as a “fleet” or as a “chain”.  This is much more than a passive “help desk”.  One example is where specialists use real-time benchmarking and other tools, working with new business processes with the physical assets and the dedicated workers, to unlock value of themselves and the physical assets.

In the following diagrams, a team is located in different sites at the moment.  This example has 4 physical assets, A through D, and specialist 1 is mobile (working from a hotel, home or in an office within the enterprise), and specialist 3 is in an operations center.  In the left-hand diagram, specialist 1 is supporting or improving the performance of physical assets A and B, and specialist 3 handles the physical assets C and D.  In the right-hand diagram, a change in performance in asset B triggers a workflow and specialist 2, who is on call or is assigned by the team supervisor, handles asset B.  Specialist 1 does not receive workflows for asset B unless the team supervisor changes the assignments.  Overlapping assignments are also used, especially when multiple disciplines or specializations are involved.  Both use the same integrated and federated information, and these specialists become champions to help all like operations and equipment improve performance.

In the following diagram, a workflow “brings the work to the worker”, using the same integrated and federated information, on-line performance applications, and human workflow.  The supervisor(s) can easily change assignments, and the workflow can include escalation, which can be guided by the performance applications’ output compared to thresholds (simple calculations of time to reach a threshold).

The strength of these workflow is to help specialists intervene early enough, using standardized and trustworthy data, focused on trends.  This processing of information is automated as much as possible.

The specialists spend most of their time working on improvements instead of processing data and analyzing previous performance problems, and their decisions.  As a result, major overhauls are safely and reliably delayed, equipment performance is improved, and operators trust the equipment more to help increase performance at each physical asset.

Why is the (Level 2-3) platform key to the future state?

I seem to end up in many discussions between IT/OT, the convergence that is required in order to achieve today’s agility. It is really is the transition of existing operational / business systems from “open Loop” to “Closed Loop”. For many of us from the control world this is just extending the “closed loop” control approaches to the supervisory/ operational architectures, but with longer periods.

Holacracy a New Way of Work can it Apply in Industrial Operational Space

I have spent the weekend listening a reading more on Holacracy, (http://www.holacracy.org/) and attended a training two weeks ago. While the concepts are familiar to me in that it follows the AGILE Software thinking and approach to putting a framework in place that enable :

·         Agility through understanding where you are and what you have to do so you can make changes

·         That enables empowerment of the team, individuals

·         The distribution of authority to enable empowerment to execute

The whole approach makes total sense to the new operational transformation environment, and I believe could be applied to manufacturing. Providing a framework for the more efficient execution, planning of work across an organization.

If you look at the Agile case studies from John Deere where they applied agile , top to bottom the results speak for them selves:

While agile is applied in the software work, what we seeing in industrial operations, is not a transformation in technology (yes it is being enable by technology) but it really is a transformation in the way companies plan, execute, work. This work could be planned work from a business side, to work generated on the plant that needs to followed up a resolved, shifting workers from an average of 35% planned work in a day to greater than 70%.

Holacracy and Agile are systems that transform the way in which work is planned, and executed, with constant empowerment of people to change and evolve the system.

As I look into both frameworks and try to apply them in my own life, I cannot see why they would be a possibility for transformation of culture to achieve better work in the industrial work space.

It is important to note both systems are aligned and they are a framework, they require discipline and execution within the framework to enable the agility. Too often in manufacturing and the industrial space people put technology and systems in as “silver bullets” and expect them to solve everything. But they are only tools, there needs to be an operational cultural transformation as well and combined you gain real change.

If you have not heard about Holacracy and are looking at a transformation in the way your company works have a look at it.  http://www.holacracy.org/, there are many You tubes and discussions on it!

What kind of a “driver” should the front-line worker be in the factory of the future?

This is a question I get asked a lot, and it is valid question. With the change roles, changing scopes of responsibility, and changing demographic / way of working, certainly the generic roles of the past 20 years will not work.

But getting back to the “driver” type of the future no matter role. So many people say why not eliminate drivers and humans all together, nothing new this is “lights out manufacturing” but is it practical. I believe not and the reason is the demanding world of today which demands change. 

Certainly where we have consistent planned know execution automation makes the whole sense, but :

•         our product run sizes are reducing
•          product change overs are increasing
•          new product introduction is increasing
•          Agility is key

The ability to absorb and handle change in operations, products and personal is becoming foundational in our operational system of the future.

Imagining the possible – if we didn’t have the burden of IT legacy

For years organization, IT infra structure/ architecture have caused silos, and boundaries to be set up between departments and different levels in an organization. The IT/ OT convergence of has been driving to integrate or break these down, but too often it is gluing the existing structure and with this comes a lot of the limitations of the original structure.

Many IT systems have institutionalized the “pyramid and boxes” design…along with its fundamental design flaws that are at the root cause of our integration challenges. The different streams have different time, different context, different language. This drives the glue to how to map these different context/ time slices etc.

Imagine if we took a different approach of “integrated digital streams” aligned centered on the product/ service for the customer/ market. Imagine if you could have a system as shown below:

From static silos of data (low-res snapshots) to integrated digital streams (high-res movies), where the streams of data are aligned , captured for one goal of competitive delivery. 

This requires a different thinking to the traditional IT, and too often when engaging customers they are struggling with gaining this operational agility, often hamstrung by the traditional organization/ and It structures. 

The diagram above provides a vision of if we were freed to think of solutions outside today's boundaries.

New World of Work will be center to Factory of the Future

Last week at a conference, a couple of my colleagues and I had the opportunity sit and debate the changing world order that will make the “factory of the future”. The three of us are involved in the major opportunities we see in the market and it provides us the real opportunity to engage with companies with transformation plans, and engage with thought leaders. We decided to approach the discussion of the future factory by approaching it from different industries, as well as markets.

Sure enough we ended up aligned on the core to the “factory of the future” will around what two companies labeled “New World of work”. I have mentioned this many times in this blog around “smart operational work”.

We were able group companies who looked at the future thru "new technologies" and how they could apply them, (I seem to visited a number of this type in the last month) vs those companies that we believe will be the leaders with the successful approach of “how they must operation, work” in the new world.

We defined the new world means the next 5 to 10 years with characteristics of:

•       Brand loyalty at customer reducing, so “Brand Promise” is key
•        Agility to satisfy is key
•        Shrinking mid tier market as the larger companies continue to consolidate to address the supply of new products and service markets. (especially in consumer products).
•        Dynamic workforce where workers rotate locations/ roles, experience in a role will be less than 2 years.
•        Supply chains with limited inventory requires transparent/ agile manufacturing across the sites.
•        “Constant Change” in assets, process, people, products is the natural state in the 2020.

The diagram below is an interesting on Agility:

The Sense of time shortening causing the decisions, lifetimes of products and lines and roles getting for ever shorter. The ability to rapidly introduce, change in not just product but also delivery, and supply is key in order to satisfy.

The fact that each of us engaging different industries such as oil and gas / process, to consumer manufacturing saw the core catalyst the leading companies have identified as the transformation in the way their company must react, capture and execute work. Shifting from isolated plants, and people to teams of plants and people that work as an aligned operational team to achieve a goal.

The “New world of Work” is fundamental built on :

• New ways of working with dynamic workers that share, collaborate and are connected but assume experience from the system, they trust the system
• New Processes around agility, new product  introduction that leverage the skills and approach of the “digital Native” collaborative worker, combined with new technologies to enable new processes and operational awareness. The ability to see situations early, continue to learn, and act fast to changing conditions is key.
• New technologies provide the opportunity to deliver these new ways of working, with new processes. The likes of leveraging the data, through “big data” to use the past to determine the future in a natural manner. The industrial internet of things (industry 4.0) will enable smart devices providing new levels of embedded autonomy in machines and processes, shifting workers to “exception based” management, but with greater responsibility.

The diagram below shows this shift, which will require different tools and approaches.

So as you look at your plans, are you stepping back and looking at the way you will work, then understanding the profile of operational team, how they will developing the processes to satisfy this work and required agility, and then looking at what technology you can leverage to accelerate the success in a sustainable and evolutionary way. This last comment is key as the natural state of the new world is one of “change” and the systems and culture must be able “master” naturally.

Is the day of User Guides / Manuals coming to end as Learning and Guides Merge???

I constantly work across teams, and companies, and listen now to challenge of the “dynamic workforce” that is rotating on sites and the challenge of “knowledge management/ transfer” constantly raises it’s self.

I was going to do a this weeks blog on a different topic, but a call this morning and one yesterday from engineering partners and customers around “knowledge transfer” and need to reduce the “time to experience” constantly comes up.  So I decided to chat about this challenge.

We have it within product development, how to transfer knowledge to field and set learning just does not work, so “self service” “E Learning is the big thing. But what the engineering house wanted to discuss was about their traditional project documentation, as they feel they waste a lot of time on documents that get out of date, and in many cases are not used.

This is again the same debate we have internally and I read in the forums as the traditional “User Guides” are giving way to videos, and then people debate what is the difference between E Learning, and user guides.

The question was asked why can’t our user question experience be short e learning's, and then if you have someone who wants to end to end learning these short E learning's and structured for a logical flow.

This is certainly where the software market is going, and seems logical for the Solution market. As the solutions developed on stand product need to evolve to solutions, the “learning experience” has to shift to in line, and native.

We have seen out operator training systems accelerate the retention, of data, and process for success. Shift to experiment and hands on, visual experience has an impact. This leads to the discussion of if video, recordings, , embedded simulation cases need to be part of the knowledge system.

Without a doubt “knowledge transfer” in our dynamic world is key, and maintaining the value of knowledge in a form that can easily consumed.

What is required is a knowledge system that:

·       Enables natural access in the context

·       Access remotely on different devices

·       Ability to easily add new knowledge and information.

·       Knowledge Management is key to tune, clean up knowledge, so the system is effective 5/ Rich search ability

The key here is an open system that enables crowd sourcing of information from many different roles, from within the company and from outside, but those who can contribute. The challenge in the industrial world traditionally contribution from roles was limited, this was due to main reasons;

·       The culture and atmosphere have not promoted the sharing, contribution

·       The systems did not enable natural, easy contribution, to one place that enables effective information.

Both of these factors are in transformation:

·       The systems / technologies are now available for knowledge, information systems to common, and easy to use and contribute. A notable example is Wikipedia that has millions of people contributing, and millions using. Key is it is simple to add new and extend knowledge posts from where ever you are. But they have a common hosted system, and they have a team of people reviewing and managing the information, so the system' s value is maintained. But I doubt the “word” is the best mode for rapid intake.

·       The culture of gen y is decidedly different to baby boomer even early gen x, they naturally search, share and contribute. Without this cultural transformation,  the concepts of Wikipedia and Facebook would not have worked, and grown to become such a natural part of the modern lifestyle.

It is time that the concepts of a Wikipedia / Youtube capability become a natural part of the industrial landscape, where the tagging of knowledge can provide the context and linkage with the supervisory system. The supervisory system must naturally call this knowledge system, passing context, and the natural ability to contribute and search.

All operational people no matter device should feel, like they do on Facebook, to add comment, capture events, capture experience from the system, and tag with context to increase search ability and use.

So will we have user guide/ solution manuals or will evolve to online learning, that is adhoc, and evolving vs a “snapshot” in time.

Operational Continuity Foundation is Rapid / Early Decisions by Systems and People.

I was involved in an interview last week for an article in a magazine, like so many of these we had an expectation of the subject the editor wanted but as started it was clear that subject and expectations where different. Basically the editor wanted to understand about “big data” being applied in a particular industry, again it was someone with a technology concept the market is throwing about vs really understanding the business / operational challenge the industry is facing.

It did not take long for us to evolve the conversation into the number the main things companies must harness:

• Operational Continuity: Maintaining their producing plants at the maximum output, with greatest efficiency, and best product margin
• Agility: to supply the market with the correct product at the right quality, and right price and the right time in an every dynamic market
• Asset Management/ Utilization: This is both fixed, mobile capital assets (non breathing assets, such as plants, trucks, ships) and the human assets (breathing assets). We find that as globalization increases the buying and selling of capital assets increasingly happen, introducing of challenge of  how do incorporate existing systems, automation, and practices into your overall value chain to provide the above “Operational Continuity” and “Agility”. Same when the asset is sold how you dis engage it cleanly especially with IP in the products and process. Combine this with the dynamic Human Asset landscape where human assets are moving regularly between plants and locations. Causing on a site not to have the required experience to make decisions, but people are in a role of having to make the decisions. YES the asset world for both capital assets and human assets is shifting form traditional stability in both classes for the last 20 years to one of both dynamic.

This comes back to conversation I started last week around “Achieving Consistent and Right Results in an Agile World” and the need for systems that have both:

• Embedded knowledge and experience: key in this system is have a culture and system that naturally enables knowledge to captured and arranged, managed to be current and while native consumption of this knowledge is simple.
• Augmented Collaboration of Experience: That in this dynamic world the need for a community of human assets of different experience in role and locations to contribute naturally to a decision in real time, augmenting the embedded knowledge. 

This calls for a system that enables people and systems, all of different levels of capability, and experience to work in coordinated way to reach a decision and act. The above diagram is a simple one of the core items of Action orientated Augmentation system.

Unconditional to success is:

• Detect the situation requiring attention as early as possible, pin pointing the location and cause as best as we can. The traditional alarm, “as is” is too late. This does not apply just to process situations but also operational/ supply chain situations that effect “Operational Continuity”.
• Understanding: This means the right person, or people, or system is notified with the required context of the situation. To often transitional systems are application based, so you alarm to control room, or SCADA system. There needs to shift to notify to people and roles, with acknowledgement of acceptance so that correct people are investigating and acting. Yes this will mean systems require unique logons, and shift to named users as people will be connected more, across applications and devices, and accountability in a team situation is fundamental so tasks do not get dropped. But core to understanding is the ability not to be just notified but to investigate, from the provided context the situation based on the workers experience, to collaborate fast with peers, and contribute an opinion.
• Decide: Based on the incoming opinions from systems, and people, and raid decision can be determined based upon experience, knowledge, and technology. The decision could be made by a system or person based upon the inputs.
• Actions: The appropriate actions and process to resolution can then taken across people (one or many) and across systems.

All the way along the system will rapidly manage the process of detect, understand, decide and act, and then track the success and increase the embedded knowledge. 

This is not a question of a new technology like "big data" it is about having a framework that works across your operational landscape to empower people, and systems to leverage existing knowledge and experience to evolve the Operational Success of the company.

Achieving Consistent and Right Results in an Agile World

As Sunday draws to a close, I sit out looking over to pacific the waves crash, and birds fly, it is my time of reflection.

Last week I talked about some of the observations from the last month on the road. But this week I debated with a number of thought leaders and we all aligned on the challenge of a dynamic workforce, and dynamic operational/ business environment, means that chance of “Lights out Manufacturing “ are slim.

One company I was engaged with last week their thought pattern was still about replacing the personal on the plant, going to total automation. While I agree with automation, it is required for consistently and velocity of production. But I struggle with agility.

Two days latter I was at another company and they were all about empowerment of people, they wanted to automate process, and operations to free up people to add complimentary agility and “out of the box” thinking.  As one C level said to me, our market is changing as fast as we ever seen, and

Stepping back and looking at both these companies the second company was more automated than the first and the second was investing in automation more than the first. But their attitude was to gain consistently and free up people from repeatable tasks, and increase the responsibility of people, and empower people to make decisions fast.  

The diagram below really depicts what I started to introduce last week, and what this second company believed in.

That they needed to design their systems and people to play “natively in the dynamic world”, and they have realized that “embedded Intelligence and knowledge” will be key and must grow proportionally with increasing data. They also realized that with agility comes the changing operational environment and situations which will require “augmented intelligence” with the human brain can work out. The key thinkers in the industry are not looking to dependency on 1 to 2 people, they are leveraging the concept of “crowd sourcing” thru a active community of people. As we look at the operational/ automation world of the future the key pillars will be:

•     Ability to capture knowledge and intelligence into the system to automate process, and operations. Key is this is not just traditional automation in PLCs/ DCS etc, it is capturing repeatable knowledge and decisions. So the system must bread a culture of contribution and use natively.
•    Ability to have a community of workers who can share collaborated “naturally” with ease, no matter the location of the users and state. Foundational to this is  the ability trust the information, the measures so a common understanding of the situation, and basis for decision can be made.

Leading to natural decisions, and action paradigm across the team as seen below. I will expand on this more next week.