This year, the number of connected devices will increase 30% above last year, according to Gartner’s predictions. That amounts to 6.4 billion connected things across the globe. That level of connection opens up a whole new world of possibility for greater efficiency in industry.
For Japan's Fujitsu, using the Internet of Things (IoT) in the factories enables greater efficiency and reduced cost as a result of identifying obstacles in processes and addressing them in real time. Takaaki Suga, head of the company’s IoT business division, wrote about the ways in which IoT has resulted in more efficient operations, greater productivity, and reduced logistics cost for his company in The Unfolding Value of the Internet of Things.
One of the ways IoT increases efficiency is in setting up predictive maintenance for the equipment. That information comes from the data taken off the machines themselves with sensors that signal when maintenance needed before it causes a problem in production.
Drawing together data from multiple sources in real time
The story of improving factory operations begins with getting information about it in real time, and that requires managing multiple streams of data. As many forms of data, including the actions of both human and machine, are involved in operations, they all have to be taken into account in context of how they correspond to and influence each other.
IoT makes that possible by pulling in multiple streams of data from sensors in real time, putting it all together in the cloud and working through the necessary analysis to visually represent the causal relationship.
For example, at Fujitsu’s factories a single line is used to produce more than a single product. Consequently, the settings on the line have to be adjusted whenever the production shifts to a different model, something that typically is required more than once a day. Then the calibration has to be set, and IoT can ascertain that it is done correctly, taking into account all the data involved, including the employees, the machines, and the setup within which they all work together to create “a comprehensive picture of the entire process and the bottlenecks that slow it down.”
Sticking to the schedule
Eliminating bottlenecks is particularly important when one has to maintain quality standards while meeting deadlines for a set number of pieces to be ready for pickup at a particular time. That was the situation at Fujitsu’s Shimane PC factory, which in collaboration with Intel, implemented an IoT solution that reduced delivery costs by 30%.
Maintaining quality control at Shimane Fujitsu necessitates identifying any imperfect parts to be taken out of the assembly line and moved to a different part of the factory for repairs. The problem was that knowing something was in the repair area was not the same as knowing when it would be ready as there are various stages of repair with different durations of time.
That meant it was impossible to predict with absolute certainty when that product would be complete and ready for pickup. That resulted in inefficiencies such as delayed deliveries or even the expense of ordering an additional truck to complete an order that was waiting on a part in repairs. Fujitsu’s solution to the problem was to apply IoT to identifying stages of repairs through visualized location in real time since different stages of repair take place in different locations of the repair room.
With a beacon sensor, a barcode reader, and PC tracking to visualize the exact location of each item in real time, employees were given a clear picture of where the item is and how far it has to go. They could then check on the status of the item, the date it is supposed to ship, and how far along it is in the repair process so that they can be sure it would get done on time. Knowing when things will be done eliminates the necessity of special deliveries for late items.
IoT’s boost to productivity at Fujitsu is extensive because it is not just a matter of making the machines or employees work more efficiently. It pulls together all the pieces of the production puzzle to improve the whole, which is greater than the sum of its parts.