Big Data, Mobile and IoT Remote Monitoring
Big data, mobile and The Internet of Things (IoT) remote monitoring are transformational to the automation of business processes. But how does big data, mobile, and IoT help you improve your operations?
To conduct an ongoing analysis of your business and improve your operations, your business processes must be evaluated in light of big data, mobile, and IoT remote monitoring.
Big data is a term that’s been around for a long time.
Analysts describe “big data” in terms of the 3 V’s:
- volume (amount of data)
- velocity (the speed with which data is gathered and flows through your systems)
- variety (the kind of data that’s available)
Make Big Data Small
To make things practical, you need to make big data small. Making big data small – meaning actionable – is the way to actually improve a business process or answer a question that you ask everyday in your business. You can apply big data to facilitate your processes, monitor assets remotely, maximize capital spend, and project return on investment.
Most often, from a business perspective, you’re collecting data to review and validate your business processes. There’s another variant of data that’s enabled by the “things” that you’re attaching to the Internet. More advanced hardware at lower costs provides information in real time about the condition and location of “things” and enables remote diagnostics and even remote service. For example, equipment, refrigeration units, HVAC systems, are being equipped with sensors, so you can better understand your business processes and make smarter decisions.
Own Your Data
“Things” can’t communicate without a mobile communications infrastructure. Mobility is also about putting information in the hands of stakeholders throughout the service supply chain – no matter where they are – so decisions can be made.
When you connect the cloud and security with high-speed wireless networks, you have an enabling force for IoT. A critical factor for IoT is utilizing the big data from tracking these “things”. To make the data frictionless and improve business processes, you must own your data.
The convergence of big data, mobile, and IoT is being fueled by connected devices. The price of devices is falling. The computing firepower is rising. The value of connectivity is increasing.
Enabled by big data, mobile, and IoT, everyday physical objects can be connected to the Internet and can identify themselves, offering the opportunity for better asset management:
- Problems can be predicted – reducing emergencies; making scheduled preventive maintenance redundant.
- Problems can be resolved remotely – technicians don’t have to be on-site; all stakeholders in the service supply chain can use their favorable wearable device to access the right information at the right time.
- Efficiencies can be gained – automating the adjustment of assets operating points remotely.
But your existing monitoring system may not be able to highlight equipment issues efficiently. You may receive a high volume of duplicate and inaccurate alarms. Employees may become frustrated with and distrustful of the alarms. With a monitoring system that’s integrated with an asset management system, your data is available in one database, rather than disparate systems. Your work orders can be streamlined, effective, and even predictive.
Get Started with IoT Remote Monitoring
How can you take advantage of big data, mobile and IoT Remote Monitoring?
1. Get a clear understanding of what you want to achieve. You must ask yourself what’s important from a facilities perspective. What really matters? Quality, safety, the customer experience, efficiency, cost savings? Investigate your maintenance practices across the organization to find efficiencies, improve processes, and reduce costs.
2. Identify the assets that you want to track. Work with the relevant suppliers and manufacturers or the people who have a detailed understanding of the assets, including how each asset operates, the data available, and how that data can be communicated. You need to determine which of your assets are most critical. Those assets should be tagged and entered into an asset management system for tracking.
Because you can track all the different “things” at the asset level, you can make the appropriate fix/replace decisions against investment thresholds to generate savings. For example, warranty claims and vendor compliance, in terms of the effectiveness in fixing particular pieces of equipment. Now you can gain an understanding of every one of your assets. Not just manage work orders, but determine the lifecycle of costs to the asset level.
3. Identify the data elements that you want to collect and correlate. There’s structured data (fields, forms, and tables). There’s also control-based or text-based information which must be correlated to be understood. This unstructured data is pulled into a data warehouse and a sophisticated rules engine provides recommendations. This data management system becomes your central hub to access data in a usable format.
4. Work with your software vendor to define and refine the rules that will leverage and transform intelligence from the data to ultimately drive action. You need to utilize data in such a way, so that you’re doing the right thing at the right time with the right person. You need to reverse-engineer your maintenance activity. Start at the repair and work backwards to understand what went wrong in the first place. This analysis will help build the rules engine.
5. Correlate big data to predict future failure. For example, telemetry data is the remote measurement of equipment, collecting and transmitting data to receiving equipment for monitoring. With telemetry data, you can predict the asset will fail within a 3-10 day period. If equipment isn’t operating within established parameters as determined by correlating its telemetry data, there’s usually a spike in energy. Less-than-efficient equipment typically uses 20-30% more energy than it should; an indicator of a potential problem.
Through predictive maintenance, you can schedule work orders in advance for more efficient labor management. With predictive maintenance, you can reduce the volume of alarms, increase equipment uptime, identify energy usage which drives savings, as well as improve the quality of work and the positive impact on customers, employees, technicians, and third-party contractors.
What starts as a technology project can realize tangible results from a people perspective, especially for problems during off-hours. In the past, when something broke, technicians had to arrive as quickly as possible and repair the equipment as quickly as possible. Now, you can predict when equipment is going to fail and schedule maintenance activity accordingly.
The concept of predictive maintenance is applicable across various industries. Previously, it would have been difficult to correlate savings. But predictive maintenance changes that. You can reallocate budgets to improve the customer experience and maintain trust in your brand.
Improve operations with big data, mobile, and IoT remote monitoring.