There’s an old proverb that says the “proof is in the pudding”. The original meaning was that you had to try out a food before you could determine whether it was great. These days, a great deal of companies approach industrial IoT a whole lot like that old proverb.
But despite unprecedented adoption projections — IoT spending in 2016 was already at $700 billion expectations for $1.3 trillion by 2020 — an astonishing number of companies are still hesitant to take a seat at the table.
There are reasons why many are reluctant to move forward. A large number of companies are worried about safety with around 62% worried about cyber risks that may damage their operational abilities and brand names.
Others are worried about standards and protocols that have fully half concerned about standardization issues. It seems nobody wants to get caught out in the cold having adopted the”wrong” platform.
But one crucial reservation centers around the issue that could be the driver of the legitimate business value of IoT engineering in manufacturing — analytics. And as the pace of adoption quickens globally, fully 60 percent of companies don’t have the analytical capability to utilize the data collected from connected devices and benefit from its core value.
The Value is in the Data
As it turns out, the mountain of potential data accumulated by IoT apparatus is the real source of value in manufacturing IoT. So, if data is king – or in this case pudding – what benefits are achievable?
A company can be saturated in connectivity, but what will drive process improvement and cost reduction is the ability to analyze the data, automate decision making at a pace faster than human decision making may ever achieve and also to deploy solutions to capture benefits identified inside the data. Here are a few ways that data analytics can drive IoT business value:
Better Shop Floor Control: The obvious place to start is the store floor. Through IoT connectivity, manufacturing companies with the right analytics platform can streamline their processes.
This can be done through practical applications such as planning and monitoring to ensure the suitable production rate without over or under generating. Or, it could be more robust by deploying platforms that utilize machine learning to hone production volumes in real time with no human intervention.
In summary lot/high mix environments, data analysis can plan changeovers and installation of human assets to maximize changeover time and reduce idle time across the factory to increase Overall Equipment Effectiveness (OEE).
And, predictive maintenance can identify problems before they happen and schedule the appropriate repair at the most efficient period (For example, bearing tracking software may indicate that an overheated bearing can be scheduled for replacement through an upcoming changeover. This reduces unplanned downtime by replacing when the machine is scheduled to be down instead of waiting till the part eventually fails).
Utilizing IoT in combination with the right analytics platform at the shop floor level reduces raw material waste, improves equipment up time and allows more precise and automatic manufacturing adjustments during the run to maintain quality.
As processes become more efficient and cost effective at the shop floor level, value is realized through the enterprise.
Stretching the Field: In sports, the term”Stretching the Field” is used to refer to a player whose strengths are so extensive that it increases the reach of the whole team into parts of the field where it was formerly limited.
Manufacturing IoT technology brings with it the value-added capability to extend the field in several ways by allowing manufacturing companies to use data away from the factory to enhance processes within.
One way manufacturing can stretch the field is via more accurate consumer data for real-world use of products.
By monitoring and analyzing actual consumer use, accurate data can be contained in manufacturing planning, warranty planning, parts inventories and other aftermarket or service related areas that impact production.
In addition, it also helps companies who create seasonal or perishable products to narrow their manufacturing windows and plan more accurate and cost-effective forecasting based on real-time usage data.
Manufacturers can also stretch the field from the other direction by linking the factory directly to their distribution chain. Internally, this means that inventory of raw materials and elements are not just tracked.
As materials are utilized, the system can check on hand versus allocated and review current programs or forecasts. It might then assign generation based on tracked in-bound material and vendor lead times and place orders as needed to maintain optimal inventory — all without human interaction and with much more accuracy.
ERP Enhancement: While ERP systems and IoT might appear to be an instant match, many companies have not fully realized the value in linking the two to allow ERP systems to leverage the power of linked data.
One study indicates that only 16% of marketing managers, contracting managers and execs consume IoT data inside their ERP system. However, using an enterprise spanning ERP connected to all crucial business systems, there is value in integrating manufacturing IoT connectivity.
Enhancing ERP capability with IoT data would have two key advantages, both of which add value to each system.
First, it improves data availability and provides key decision makers such as supervisors and execs to make better informed and more precise business decisions. With a better understanding of what is happening on the shop floor through access to this data, other functional areas within the ERP are also enhanced, such as customer service, scheduling, planning and inventory management to name a few.
Second, communication is enhanced through the enterprise. This includes communication between internal stakeholders who now have complete access and analysis of the data.
Moreover, it also has improved communication between vendors on the distribution chain as well as customers who use the company’s manufacturing and whose data can be contained in current production forecasting.
Value perception is a subjective concept driven by many factors. But real value that is expressed in dollars saved or new business expansion is much more than perception. It is just good business. The volume of data provided by the IoT must be paired with analytical capabilities to leverage its inherent value.
Those companies investing in such platforms are already reaping the benefits and gaining an edge against competitors. And for those who have yet to start their IoT travel, I suggest they try the pudding. Based on current outcomes…it’s very very good.