More and more data is being collected and stored daily, with manufacturing leading the trend by generating about twice as much data as government, the next largest data generator. Organizations know there is value in this data, but much of it goes unrealized due to the complexity of creating actionable information. Traditional solutions haven’t delivered on promises made, but new industrial software applications (apps) are changing this paradigm.More and more data is being collected and stored daily, with manufacturing leading the trend by generating about twice as much data as government, the next largest data generator. Organizations know there is value in this data, but much of it goes unrealized due to the complexity of creating actionable information. Traditional solutions haven’t delivered on promises made, but new industrial software applications (apps) are changing this paradigm.

As with apps for smartphones and tablets, these types of industrial apps are becoming a common way for vendors to supply software to end users, supplanting more traditional software solutions. Like smartphone and tablet apps, these industrial apps are lightweight and low-cost, and require very little in the way of corporate IT support.

Older solutions required collaboration among IT specialists, manufacturing engineers and data scientists. IT specialists created and maintained the infrastructure needed to host heavyweight data analytics software solutions. Specialists were also needed to install the software, and to set up client-server architectures for users. Industrial apps address these issues by simplifying required IT efforts.

With older solutions, manufacturing engineers identified problems they thought could be solved by analyzing data, and then turned to data scientists to interact with the data analytics software and produce results and reports. Once this was done, the manufacturing engineers often required several iterations to hone results, which once again required the assistance of data scientists.

This methodology was very expensive and time consuming, and often ineffective because it:

• required significant upfront investments in software and hardware
• didn’t deliver results for months, sometimes more than a year
• made ROI very difficult to determine upfront, increasing investment risk
• required close and ongoing cooperation among IT, data scientists and manufacturing engineers
• needed data scientists with at least some knowledge of manufacturing, a rare breed
• made the iterative method of problem solving very difficult, which is often the best way to apply data analytics to the large data sets found in manufacturing

Because of these and other issues, manufacturers have been searching for practical ways to create actionable information from their data. Suppliers are responding with a new class of lightweight applications, each dedicated to solving problems in a specific area of manufacturing processes.

A Simpler SolutionWireless instrumentation and low-cost software apps make it possible to monitor pumps, steam traps, heat exchangers and other equipment for a fraction of the previous cost, and in much less time.

These software apps collect raw data from wireless and wired instruments, and perform analytics to determine the condition of plant equipment and assets. This provides greater visibility into operations, enabling improved reliability and energy efficiency.

These software apps use pre-built analytics with embedded domain expertise to diagnose the health of plant assets. The resulting information and insights can be accessed and visualized on a web-user interface running on PCs, laptops, tablets or smartphones (Figure 1). Dashboards and charts make navigation and interpretation of information simple, so minimal training is required. The apps include features to ensure security, including role-based access.

Figure 1

Figure 1. Emerson’s Plantweb Insight apps can be securely accessed from any device capable of hosting a web browser including PCs, tablets, and smartphones.

Each of these apps is purpose-built for a specific asset, making them quick, easy and inexpensive to implement. This contrasts with general purpose data analytic solutions, which often require extensive configuration or programming by the end user to yield meaningful results, and the efforts of data scientists versed in manufacturing.

Typical examples of equipment lending itself to wireless monitoring and app-based solutions include:

• Steam traps
• Heat exchangers
• Pumps
• Pipes and vessels subject to corrosion
• Relief valves
• Safety shower and eye wash stations

Analyzing data from each of these areas can deliver significant bottom-line benefits.

For example, determining exactly where energy is being lost tends to be a challenge when companies try to implement an energy improvement program. Energy losses occur from heat exchanger fouling, failed steam traps, process unit inefficiencies and other causes—all of which may go undiscovered from lack of key energy measurements and analysis.
By expanding wireless instrumentation and pairing it with the right software apps, the appropriate data can be obtained and quickly analyzed, producing results identifying where problems exist, and providing insight for taking swift corrective action.

Using this approach coupled with industry experience, a 250,000 barrel per day refinery could realize the improvements/savings shown in Figure 2.

Figure 2: Typical savings in a 250,000 barrel per day refinery.

Other examples:

• Steam trap monitoring was installed at a chemical plant in Germany. They calculated a return on investment of less than two years, thanks to savings in energy costs. They also achieved substantial additional savings due to the reduced number of process shutdowns because of steam trap failures, and eliminated the need for maintenance technicians to make regular rounds.
• A similar steam trap monitoring solution at another plant increased production by 12% and saved $100,000 annually in preventive maintenance.
• A refinery installed a pump monitoring solution that avoided pump fires and associated shutdowns for five straight years at 1/10 the cost of other solutions.
• Another plant installed a pressure relief valve monitoring solution, resulting in a five-month payback and total annual savings of $3 million.

Virtually all process industries, such as refining, chemical, power, food and beverage, life sciences, etc., have the same or similar problems, which can be addressed by wireless instrumentation and apps.

Conclusion

Wireless instrumentation and accompanying applications simplify the installation, configuration and maintenance of equipment monitoring systems. These systems can be brought online in hours or days rather than months, and often at a fraction of the cost of traditional wired instrumentation coupled with large and complex analysis software. In most cases, payback is achieved in a matter of months, and an initial system can be installed at minimal cost to prove viability.