Edge computing is currently applied by both discrete event manufacturers and continuous manufacturing facilities to capture shop floor data and other data processing tasks. The adoption of the industrial edge has also accelerated the integration of Industrie 4.0 business models, which bring its own benefits. These benefits include machine optimization and enhanced productivity, among others. To better understand the benefits of adopting industrial edge solutions, practical case studies paint accurate pictures to which manufacturers can relate.
This article will discuss:
How manufacturers make use of industrial edge computing
Highlighting industrial edge applications through case studies
Benefits of adopting the industrial edge using practical case studies
Adopting the industrial edge in manufacturing
Adopting edge computing starts with defining or determining an application case which leads to forming a usage strategy. The application case could be as simple as capturing machine data to learn more about machine utilization or as complex as controlling automated systems within the shop floor.
Once an application case has been determined, a strategy for deploying industrial edge hardware or IoT devices to handle the task is required. The following steps can be used in creating an industrial edge environment for data collection:
Determining and choosing the industrial edge hardware to be used on the shop floor
Choosing between an industrial cloud or IoT platform to support the edge devices
Selecting edge applications for processing edge data
Connecting shop-floor systems to the edge hardware or integrating the hardware into existing IT operations and systems
Developing a processing pipeline that combines both edge and cloud computing applications
With these items and concepts in place, the facility brings latency processing closer to shop floor equipment. It also sets up a symbiotic relationship between the industrial edge and an external data center, which is the cloud in this case.
Industrial edge application use cases
The diverse ways in which the industrial edge can be applied requires multiple practical cases to accurately explain the importance of edge computing. Here, three case studies highlighting its application in enhancing overall equipment efficiency, enabling predictive maintenance, and increasing productivity will be provided.
BC Machining improves machine utilization with industrial edge
BC Machining is a contract manufacturer that produced machined metal parts for the US Department of Defense and the automobile industry. The enterprise made use of 12 computer numerical control (CNC) machines to produce metal components. Although these machines are digitized, BC Machining struggled with tracking machine utilization. This affected its productivity and ability to constantly meet orders.
To optimize its machine use, the enterprise turned to the industrial edge. Within a week, edge devices were collecting data from machines. Human-machine interfaces for operators to log hours and reasons for absences were hooked up to shop floor equipment. A smart TV and Google Chrome sticks also served as IoT devices for broadcasting data of machine performance to operators on the shop floor.
The edge devices were also connected to an industrial edge platform to analyze current machine data against an optimal benchmark or historical data. Within a month, BC Machining was able to track machine utilization on a day-by-day basis, as well as understand the cause for underutilization. At the end of 3 months, the enterprise recorded the following benefits:
A 10% increase in its OEE calculations
A more informed understanding of its machine and production capacity
Enhanced collaboration between operators working on the shop floor
An approximate $2000 spend to set up its industrial edge environment against a 10% increase in productivity
Developing a predictive maintenance strategy
A contract manufacturer who produced machined parts for diverse industries made use of 10 lathes and CNC machines to process received orders. The lathes made use of tool bits which hollowed and shaped metal continuously to get the finished part.
The constant vibrations and force employed by the lathe machine caused wear and tear to areas such as the headstock. This also led to irregular replacements of parts such as the lead screw which, in turn, caused unplanned downtime and disrupted production. To deal with these challenges, the manufacturer integrated the use of industrial edge hardware to track the functions and health of its lathes. In this case, sensors were attached to the machine which tracked its vibration and working speed. Smart devices were also attached to the machines to visualize the data collected by the sensors and connect the entire operation to an industrial cloud platform.
With the collected data and benchmark data, the manufacturer was able to note resource-intensive activities or projects which tasked the equipment, as well as, less tasking activities. The ability to track the effect of projects on machine components ensured the manufacturer was able to approximate the working durations available to individual machines before their parts became defective. Thus, with the knowledge the application of industrial edge provided, the manufacturer got the following benefits:
Machine data that enabled the optimization of machine use
Machine data provided the foundation for developing a predictive maintenance strategy
Drastic reduction in unplanned downtime, which optimized productivity
Eliminating downtime with industrial edge computing
Wiscon Products, a parts manufacturing firm that uses advanced CNC precision machines to manufacture parts, struggled with discovering the leading causes of its downtime and understanding its cycle time. To accomplish this, it needed to capture accurate data from shop floor activities, and it believed the deployment of edge devices would help.
Wiscon Products deployed sensors and smart devices to track machine spindles and their speed during operations, as well as monitor periods of planned or unplanned downtime. The edge devices were also connected to an IIoT platform which provided benchmark analysis for comparing machine performances. With the collected data, the enterprise was able to narrow down the causes of downtime and determine why certain production cycles did not measure up to benchmark production data.
The IoT platform provided the benchmark data using historical data from similar processes and the edge devices provided notification alerts any time a machine was lagging. These alerts ensured cycle times were kept to and machines ran at their optimal capacity during the majority of a production cycle. In this case, the benefits of the industrial edge were:
The provision of a means to automate the continuous tracking and reporting of machine functions
The ability to track downtime during production cycles and pinpoint the cause
Visibility into production cycles to optimize production
The applications of industrial edge solutions enable manufacturing enterprises to adopt Industrie 4.0 concepts into production cycles. With edge devices and a combination of the industrial edge and cloud, capturing data from the deepest parts of a facility becomes possible. The collected data is then used to predict maintenance, enhance production, optimize equipment utilization, and develop cybersecurity strategies in industrial settings. This is why more than 50% of enterprises are expected to adopt the industrial edge by 2021.