Do you ever feel that by the time you get a chance to research a new technology it has already been replaced with a newer version? That is how I felt the first time I heard of the “Internet of Things.” We were sitting around conferences talking about the possibility of a connected enterprise in industrial spaces and the next speaker started…“Well, I’m sure I don’t need to go into detail about the Internet of Things (IoT), so let’s skip right to how we can utilize its effect on our customers.”…and three hours of PowerPoint later…we were dead.
The IoT conversation grew exponentially fast. At that time, most of the media surrounding IoT was similar to a commodity branding campaign with bright colors and good looking people telling you they use it every day. Even if there was something to it, how could it be more of an achievement or beneficial than getting rid of that annoying dial-up tone whenever I logged onto the internet? A recent press release stated that the IoT in the manufacturing market would grow from 4.11 to 13.49 Billion USD by the year 2020. With this extreme growth, everyone is jumping on board for a piece of the profit, and many have jumped too quickly without carefully examining the risks.
“To get profit without risk…is as impossible as it is to live without being born.”
– A.P. Gouthey
What is IoT?
IoT –“the concept of connecting any device to the Internet (and/or to each other)”.
IoT in the manufacturing world is about data and how to get more of it. We can achieve this by connecting smart devices to our network and analyzing the inputs. Unfortunately, a lot of what we have seen through mass media relating to IoT in your business has been marketing to push you towards spending more money. This drive is solely related to the substantial growth estimates. I feel many have been led to a false sense of security around smart device implementation.
The Industrial IoT is not a new concept, we have lived with ever increasing IOT for more than 15 years. Recently, I noticed a good example; my smartphone notifies me whenever I need to leave for an appointment that I placed on my calendar. Several times it notified me earlier than I was planning to leave based on traffic on the most common route and saved me from arriving late. By simply applying smart devices to our lives we can be more efficient without much added risk. This does not work inside process manufacturing environments.
A recent RedLion white paper stated, “The efficiency of the IIoT (Industrial Internet of Things) model is not derived from the sheer volume of connections, but from more valuable connections, and the competitive edge gained by the sharing of information between devices and humans.”
Benefits of the IOT
Gartner estimates that IoT product and service suppliers will generate incremental revenue exceeding $300 billion by 2020 (Globally). As companies are pushing hard for a piece of the pie, do not fall into the trap of easy plug and play technology that requires zero planning.
Although there are benefits, I want to make it clear that the Internet of Things is not some unseen sci-fi super power that drifts in and out of your factory causing you unheard of 100% Overall Equipment Effectiveness (OEE) and any implementation of connected devices should be carefully considered beforehand. Involvement in the “IoT revolution” should be based around using strategic data capture to make more money for your business instead of flailing carelessly about just to be a part of the movement.
Of course, anyone in the industry can associate more information to benefits. Increased revenue areas based on increasing data collection include OEE metrics, uptime, reliability, manual input, energy output, and the ability to calculate the cost of production per equipment. The benefits are quite endless due to the many production processes and technological advances that occur on a daily basis. Overall, ask yourself what you could do in your facility with improved process visibility, extended equipment life span, and reduced total cost of ownership?
Discrete VS. Process Implementation
Remember how your life goal at one point was to build a Lego Death Star from Star Wars? You can think of building that death star as discrete manufacturing, assembling pieces and parts to make a product. These discrete facilities have led the way into the “Big Data” mentality because of the ease of execution via limited controlled parameters. We should not allow ourselves to be fooled into thinking that implementing these virtualized solutions is a one size fits all approach across all manufacturing disciplines.
Process Manufacturing would be more like making a batch of Jack Daniel’s Tennessee Whiskey. For example, one element of the process is the addition of yeast, a critical ingredient. Yeast starts to decay when exposed to air or moisture, so timing is crucial when handling and can be affected by ever-changing conditions, which need to be monitored. Overall, the final product depends on hundreds of variables that have to be taken into account for that repeatable perfect batch.
By identifying and analyzing stable common cause and special cause variations, process engineers create control practices that help in increasing the ever challenging repeatability. With the introduction of more data, those variations can be tuned even further.
Recently I was at a facility that could not run production when raining because the moisture in the air affected the final product! With so many variables, can you implement a solution worth the time and money? Absolutely! But expert consultation is the key to success. Each facility and even more so each process should be considered independently based on your strategic goals for improvement, and you should use consultants that have done similar work and understands your process market.
Get More From Your Data
It seems that most publications on the IOT has deemed Real Time Visibility as the primary objective, and I would agree that visibility is important, especially in an operator controlled environment. However, consider the following: “With great power, comes great responsibility…” We should not stop at just obtaining real-time visibility, but should continue on to using that visible data to create predictive models and algorithms that mitigate future production discrepancies to an acceptable level. Preventative action is the name of the game in modern manufacturing.
“If you don’t have time to do it right, you must have time to do it over (and possibly over and over) again.”
– J. Wooden
Are you reactive or proactive in your process? If you are always responding to the last issue, the only way to improve production is to respond faster; basically work harder. I would rather implement high-performance graphics with predictive modeling than only have the ability to react and generate a report of why we still achieved low outputs.
In that high-performance environment, the operator can see the red flags as they happen and, as the severity is displayed, predictive control is programmed to take action on pre-approved faults and requests operator intervention on the others. I would challenge you to see if you would benefit from this model by discussing it with your operators. If they can create a list of…”When that happens, I do this…” then you may be able to increase your production.
We are mostly talking about complex process systems although simple systems have their place as well. The key is to plan and think critically with experienced consultants helping to fill in the gaps. Lawrence J. Peter sums up why planning is so important: “If you don’t know where you are going, you will probably end up somewhere else.”
The IOT is growing, and there is no way to know to what extent, but many are calling it a movement that will be the fourth industrial revolution. Does that mean you should instantly jump on the bandwagon? Perhaps some more research in addition to the benefits of IOT should be completed first.
Yes, more real-time data can be used to generate increased productivity in your plant effectively; however, as data increases security threats do as well. It is important to discuss your manufacturing “wants/needs” with qualified engineers and system integrators that have experience improving processes and implementing solutions surrounding larger data capture. We have always believed that the more data we can obtain, the more efficient we can become in production. Personally, I think that is true, but the relationship between your Return on Investment (ROI) and data capture is not linearly dependent, and can change drastically with the influence of IOT threats.