Four Ingredients To Make IoT Work For Manufacturers
In order to make the right decisions, artificially intelligent systems or machine learning solutions need real-time data from sensors, RFID tags, mobile devices, and a WMS. The following article from Manufacturing Business Technology explains how four ingredients linked to sensors can ensure that IoT is being used efficiently in the manufacturing sector.
If you want to understand how the Internet of Things (IoT) can benefit manufacturers you only need to consider this scenario: When a sensor recognizes that the contents of an outgoing shipment don’t match its advance ship notice, audible alarms at the dock door sound. Employees then correct the error before merchandise is loaded on a truck and the right shipment proceeds. Sounds simple. But what’s behind that scenario – and what are the four critical ingredients that actually make IoT work for manufacturers?
First let’s start with the common denominator: sensors. Often when people hear about IoT they think about gadgets and robots – rather than the sensor infrastructure. But to put IoT to work for manufacturers, this is critical. Sensors may be only one of several pieces that address IoT challenges, but they play the most critical role in enabling manufacturers to obtain, analyze and then act upon data that can contribute to their success or failure.
Traditionally, sensors meant barcodes. While that’s still true (today barcodes feature updated functionality and enhanced data through 2D/3D barcodes), other sensor types abound. They also include RFID/NFC to track work in progress, location-based systems (RTLS, Wi-FI, GPS), M2M on the assembly line, and application specific devices (e.g. sensors embedded in products that transmit information to maintain service warranties).
While manufacturers often have many of these sensor ingredients, making them work together can be challenging. Here, then, are four ingredients for a successful IoT recipe:
1. According to a recent IDC report, “Manufacturers are looking to integrate their enterprise systems, data, and processes, to leverage new models in mobile and cloud, and apply a virtual control panel of analytics to their product, supply, manufacturing, and service processes – all in the name of achieving high-quality, innovative products.” As such, the first ingredient is a common sensor platform to integrate information from people, processes and devices. There must be a common way to get information from all sensors, interpret and then normalize the data. Because sensors typically broadcast frequently and some data tracked changes infrequently, much of that unchanged data needs to consolidated as one sensor reading. A sensor platform understands all modalities of sensors and how to talk to those sensors in one language.
2. The second ingredient is sensor data management to infer data relevance and business context (i.e. what is the relevance of the data). By putting business rules around the data, manufacturers can know if an item, for example, moves from Zone A to Zone B, or if someone without authorization attempts to check out a tool. Or a tool that is authorized for use in one specific contract is being used in error in another.
3. Process compliance to ensure data quality and exception handling is the next important ingredient. Manufacturers may have thousands of sensors collecting data, and must aggregate it and interpret it properly. As such, data quality and exception handling is vital. Exception handling may be as simple as ensuring that the advance ship notice matches what is shipped from a vendor and received in manufacturing. Today, when that information is inconsistent, materials are often put in a holding zone to deal with at a later time. In fact, manufacturers report that most of the time, no one has the time to check out those goods in the quarantined zone and so hundreds of thousands of dollars of goods are stuck in limbo. These goods are still included in working capital but in fact are dead assets. The same is true for products that were incorrectly shipped and then returned to the warehouse. Generally, new products that are shipped and then returned are stored immediately for (much) later attention. Those assets continue to add up, so ensuring that the correct products are shipped and received provides enormous benefits. Process compliance also includes putting checks and balances in place to ensure inventory is being undertaken correctly. Because the inventory numbers obtained using hand-held RFID readers is only as accurate as the hand holding it, errors are common. By establishing limits so that exceptions are noted when the process appears to inaccurate, manufacturers can audit the results immediately instead of allowing the inaccuracies to multiply and damage the bottom line.
4. And the final ingredient is actionable information via real-time alerts and integration with systems of record. Using this information, a warehouse management system can know if the wrong merchandise has been shipped out. And like our introductory scenario, an employee at the dock door will know that items are about to be put on the wrong truck and fix the mistake before there is any financial impact. Most organizations perform exception handling to avoid information overload. Therefore, knowing when a customer order is about to be in jeopardy so that immediate action can be taken to correct it is enormously valuable.
As industry analyst Michael Liard has noted, “Huge opportunities exist for players to expand their markets or capture share from peers under the IoT umbrella.” So making the most of sensors is, well, sensible. Manufacturers that include these four ingredients in the mix are well positioned to make IoT work for them.
Chris Forgione is Director of Asset Tracking at OATSystems, a division of Checkpoint Systems.
This article was written by Chris Forgione from Manufacturing Business Technology and was legally licensed through the NewsCred publisher network. Please direct all licensing questions to firstname.lastname@example.org.