How mobile can improve process efficiency for manufacturing

How mobile can improve process efficiency for manufacturing

In manufacturing processes, the rate at which goods or parts can be made, or throughput, is perhaps the most important metric for a factory. Faster production allows for more orders and subsequently more revenue. Therefore, manufacturers should try to produce as fast as possible, right? Unfortunately, increased production speed comes at the expense of quality. As the rate at which a machine runs increases, so does the likelihood for defective products.

When calculating throughput, manufactures must take into account downtime, speed loss, set-up time, breakdowns, and quality loss. By raising the speed at which a machines run, manufacturers can actually lower their throughput rate due to increased breakdowns and quality loss. For example, if a plant increases their production speed from 5 parts per hour to 6 parts per hour, but 2 of those 6 need to be scrapped, then the plant has not only become less productive in terms of throughput, but its’ cost per good produced has also risen.

Rather than increasing machine speed, factories should look to increase throughput by decreasing downtime and increasing quality. Factors such as set-up time, breakdown rate, unplanned downtime, repair time, and scrap rate are all inherent to a manufacturing system, but there are several ways that these rates can be minimized. By incorporating mobile devices with already existing sensors, it is possible for manufacturers to improve their businesses by tightening feedback channels.

It is nearly impossible to eliminate breakdowns and repairs from a manufacturing process, so in order to reduce the downtime caused by these issues, it is necessary to either anticipate failures before they happen and service machines before breaking or shorten the response time it takes to start servicing these parts. Fortunately, a mobile solution can address both of these possibilities.

With the interconnectivity of sensors and mobile devices, sensors on machines can give people on the factory floor real-time status reports for each individual machine and send alerts when machines start to run afoul. With data from machine sensors being centralized to a singular location, the mobile application, regression models can be built to recognize signs of a machine starting to break down as well as simply raising flags when data starts to deviate too far from the current process’s average conditions. By tying the machine, as well as its sensors, into the same mobile application, workers could manually control the machine’s running status from anywhere in the factory and shut down or slow down a machine as necessary.

In a similar manner, when breakdowns do occur, the machine can immediately notify a service technician via mobile application exactly what part needs servicing and where in the factory the machine is. By immediately notifying the correct person and telling him where to go and what to bring, this again shortens downtime in the system where a machine is neither running nor being serviced. In a more robust application, it would be possible to tie in the needed part information with an inventory log that could alert the worker where to find the necessary parts or prompt an ordering of more parts if necessary.

Finally, quality control can be improved by monitoring the status of batches throughout the entire system to ensure that conditions remain ideal throughout production. For a metallurgy process, one major quality factor is temperature control. If the metal becomes too hot or too cold during the process, the structural integrity of the metal maybe become compromised and lead to the batch being scrapped or completely reworked. As with the previous situations, tying temperature sensors into a centralized mobile application can warn workers when the temperature is starting to vary from its ideal state. This mobile feedback channel allows workers to see and address these alerts immediately rather than needing to be in the control room which can be farther away from problem than someone currently on the floor.

Within the manufacturing process, a centralized mobile application enables workers on the floor and close to the processes to mitigate problems before they arise and resolve issues more quickly than in systems where information is either siloed with each machine or located at a control center overseen by one person far away from the shop floor. By enabling those closest to the action, factories can increase their throughput rate and productivity, leading to higher fulfillment and higher revenue.

Steve Bowker is a Functional Analyst at Solstice Mobile. Graduating from Cornell University with a degree in Operations Research and Engineering, he is focused on the improvement of business processes through the application of cutting-edge technologies and Big Data.

The opinions expressed herein or statements made in the above column are solely those of the author, and do not necessarily reflect the views of WTN Media LLC. WTN accepts no legal liability or responsibility for any claims made or opinions expressed herein.