Augmented Productivity by Industrial IoT

Augmented Productivity by Industrial IoT

With the world running on binary, IIoT has become an imperative tool for modern business strategies 

The definition of productivity has evolved over time. At the end of the last millennium, good productivity meant workers dedicatedly spent their time on the task in hand, with favorable results. With steel replacing flesh and blood in many industries, productivity described today slightly differs from the one in the yesteryears. But in terms of mathematics, the meaning of productivity has remained unchanged; the amount of output generated within a given amount of time or other resources.

Calculating productivity may not be as lucid as it seems at first glance. It is a number derived from several variables, both direct and derived. For instance, efficiency is one of the important factors in determining productivity. But efficiency itself depends on the type of equipment, labour skill, amount of resources, and so forth. To keep it simple, let us assume the productivity of a process depends solely on the machine health and operation. With factories achieving production speeds unheard of, even a brief interruption can cause havoc. Downtime due to empty fuel tanks, over-heating, bearing damage, low oil levels and the like are highly unpredictive but avoidable with appropriate tools. 

Apart from production losses, these unplanned downtimes result in huge operational costs and an unsafe working environment for the operators. With stopgap measures to get a machine up and running, one may expect major breakdowns in the future or worst-case scenario, a serious accident.  With Industrial IoT solutions becoming mainstream space, such occurrences can be easily prevented.

Today, the evolution of technology has enabled Edge Gateways to integrate myriad industrial appliances of diverse nature in a single ecosystem. Tor IoT Platform is one such electronic ecosphere. Raw telematics solution captured from a machine has no significant value of its own. Sensibility kicks in once this standalone data is associated with other parameters to conceptualize a bigger model.  For instance, fuel level value can be used to raise an alarm to prevent a dry fuel tank. But when this value is put together with engine run hours and rpm, one can find the fuel consumption of that equipment at certain loads. 

Fuel consumption has a bigger impact on an organization’s treasury than a simple alarm. Similarly, higher machine run hours per shift may not always indicate better productivity. Diesel generator running on No-load, assembly line moving with zero production, a vehicle left idling are few of the instances where run time touches the upper numbers while the actual productive output is nought. If generator run hours are compared with units generated, assembly runtime with the quantity produced and vehicle run hours with engine RPM and location, one can get a better perspective of the actual productivity in numbers. 

Another instance can be of Induction motors, who also play a pivotal role while measuring productivity. Induction motors pulling a surge of reactive current during starting or loading is a normal phenomenon and so is the sudden drop in power factor and voltage, which is expected to recover once the motor reaches its desired speed. But consistently low power factor or voltage drops may call for special attention. Based on the past data, the user can deduce whether the transformer size must be increased, load compensation to be provided or the motor to be repaired. Addressing these might require more service time and downtime can be planned accordingly. Failure to do so can result in permanent motor damage, production loss and penalty imposed by utilities for sub-par power factor while affecting other processes as well.

Above instances showcased how a major failure can be avoided by taking the right steps, at the right time. IoT Platform enables the user to take such informed decisions backed by concrete analytics and hence more than 75% of these unplanned downtimes can be converted into planned actions. The following are some of the achievements of the Tor IoT Platforms

  • A renowned construction fleet owner saved 8% of their operational costs due to the active steps taken for fuel and asset management based on the gathered data.
  • OEMs have a major advantage in terms of after-sale services and analyzing equipment performance in various operating conditions. One manufacturer adopting the TOR IoT Platform was able to prevent several breakdowns with the help of Predictive Analytics. Their machines are expensive and serve as a critical element for the end customer. This helped reduce the total warranty costs by over 50%.

In the end, Productivity is the term around which an organization’s profitability and strategies revolve. And IIOT helps you get your decisions right every time.

The TOR IoT system is a unique and innovative approach for modern problems involving asset management and vehicle telematics. From sensor retrofitting to complex CAN integration, connect your machine to the internet and explore new ways to add value to your business. For more information, please contact www.kloudq.com

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