Applied Knowledge/ Wisdom Foundational to Internet of Things, and "Time to Performance" of Operational Teams

For the last couple of weeks, Stan DeVeries and I have been brainstorming around articulating this core area of the operational transformation, "the ability to have a system that can absorb workforce change/ turn over". Good example of this is with one company on the 2025 vision of "all knowledge/ experience in the system", this is capturing as much of the tribal "applied knowledge" that the experience operational staff are making decisions, and taking actions on and moving it to the system. If then applied in a "activity/task" based operational experience, a younger skilled user has the ability to select a "activity" and the associated knowledge/ information, and action are presented to him. Dramatically reducing the "Time to Performance" and increasing the consistency of operations, while increasing flexibility in operational workforce management.

The results of the discussions has brought the discussion around "Federated Wisdom, applied knowledge":

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/Applied Knowledge” – prescriptive advice and procedures to help achieve targets such as safety, health, environment, quality, schedule, throughput, efficiency, yields, profits etc.

The cost to store and share data has dropped significantly, and a simplistic expectation is that although storage is growing by a factor of millions in only a few years, that somehow the following pattern evolves:

Although the pattern might seem to be convenient, it is actually a nightmare, because it becomes much harder to discover and translate knowledge and wisdom from another operation, especially in another location, to the local needs.  But there is a solution.

To understand the problem better, let’s consider the definition of “knowledge” – it includes context.  This context begins with local context – time, location, process or machinery configuration, raw materials, energy and products being processed or produced.  It is already valuable to have “wisdom” to achieve and sustain best performance for the community, customers and the corporation.  This local context only needs to know its immediate information, if it has enough “wisdom”.

Now let’s consider what happens when a single site, a fleet of similar sites, or an enterprise have numerous similar operations.  How can local “wisdom” be enhanced by using “wisdom” from the other operations, especially when all of these operations are sufficiently different?

The reason that solving this problem is important is for operations transformation, such as operating physical assets as one (in a chain or as peers), and by supporting the multiple operations with a flexible team of remote experts.

One approach to solving this problem is to take advantage of a technique used in distributed databases, where a technique called “federated information” is used, especially in industrial operations management architectures.  This technique does not change the local information’s naming or structure, but provides multiple translations, both across the database for multiple similar structures, and for multiple contexts such as what financial, technical support, scheduling, quality and other functions require.  This technique is an alternative to the fragility and complexity of attempting to force a uniform and encompassing naming and structure that attempts to satisfy all applications and users.

The same approach can be applied for “wisdom”.  Currently, hobbyists and enthusiasts around the world share “wisdom”, for restoring cars, making furniture, playing a musical instrument, gardening etc.  Anyone with no experience at all can ask for “where do I get started?”, and most respondents will provide kind advice; in the same forum, experts can share wisdom that is valuable and understandable by them at their level of experience.  This “wisdom” is extremely decentralized, and the experts are providing the translation.

In the industrial operations environment, federating “wisdom” is partially automated by expanding the local context.  This expansion includes information about adjacent operations, information about the chain or peers if these operations are being managed as one, and then “knowledge” is expanded by applying the context of group targets and performance.

Some enterprises have hundreds or as much as tens of thousands of similar operations, supported by dozens or fewer experts.  Discovery of wisdom is greatly enhanced by maintaining an architecture which enhances local context without modifying or attempting to force burdensome structures on local operations.

Expect this discussion to continue as expand on the systems, and approaches to make this real, while enable sustainable operational innovation. This will be core to Industrial Internet of Things as we align smart devices, operational practices and humans into a dynamic but coordinated operational force.

"Times are a changing": Re imaging of Our World, it is flow on to Industrial Experience

As I sit on a plane heading over the Pacific again, I look around me and even my life and see how we are re imaging, or changing the way we perform daily activities. The different devices, applications change the way in which we engage with traditional activities.

Example below in the images are real:

Hotel checking happens from the applications on my smart phone instead of registering at the front desk.

In Singapore last month it was was Friday afternoon, I was on the street hoping to get a taxi to airport, initially, you think wave one down. No, not today there must have been 8 of us trying to compete for taxis at peek hour. So out comes the smart device and Über application, and I nominated a price on line for car, happy to pay a little bit more to not miss my flight, and secure a service, a win for me, a win for the driver ( he got a bigger fair).

I travel allot overseas, and I use electronic money/ wallet from my smart device to pay for immediate services when I arrive when credit cards are not available.

All of these are natural approaches to practical day to day actives and there are many more, how many of use the traditional A to Z street maps, does not even exist in the car anymore we have the GPS.

So how is this re imaging coming over into the industrial world, it is happening fast than you expect. The operational day to day life of all of us in the industrial space will be totally different in 5 years, but it has already started. With changes in company IT to enable commercial off the shelf devices into the plants, allows the innovation of industrial world to leverage these devices.

Last week I was working with a supplier with irradiation pivots for farmers. They had empowered the farms to monitor and control the moisture on their fields and control the irrigation pivots from an application on the smart phone. Replacing the need for the SCADA application at each farm, very logical. See image below.

Source "Waterforce"

Alarms and motivations now going to smart device which could be smart phone, of the new smart watches from google see below.

The traditional field worker contacting central controls room by radio, to the empower field agent, who has cameras so that control room can see the field. Plus the field worker has smart devices iPads with context to gain knowledge of current state of an area, plus information at his finger tips instead of going back to the workshop.Also best operational practices have been embedded in the field device so he knows not just the decision but the best action, and how to execute.

Training use to be going around with an experienced worker and learning from him, taking notes and taking time to come to experience. This being replace with operator training simulators, and immersive, 3D virtual environments as seen below. So now in a safe environment operators and field workers can go through scenarios, learn practices without having people in the field in danger and provide "near life experience". Much more effective than in the plant, and faster as situations can be played out, so experience is gain rapidly.

Nothing new to pilots, for years with the effect that situations the pilot and co pilot understand their role, and actions instinctively. Example the Hudson River landing 3 minutes the pilot and co pilot understood roles, understood actions. They did not have communicate hey just executed; this same approach needs to happen between the operator and field worker and even the virtual expert, and it is all possible today.

This re imaging of the industrial operational, worker day is happening with increasing speed but with it comes efficiency and empowerment, all key in agile world, and time of operational transformation.