To help small to mid-sized consumer packaged goods (CPG) manufacturers stay competitive with larger-sized enterprises, Altizon Inc. and HMS Networks today announced a partnership to offer a free First Line Analysis that helps improve, modernize and optimize a company’s manufacturing process cost-effectively and in a timely fashion.
Altizon and HMS Networks First Line Analysis
The Industry of Things World San Diego event is a leading independent IoT conference entering it’s 5th year. With over 400 registrations, it is clear the interest in Industrial IoT solutions continues to grow. This year’s key notes included presentations from National Oilwell Varco, Brose Group and Boeing. HMS Networks exhibited at the event this week with our Solution Partner Altizon to showcase our latest IoT collaboration. Check out our full summary of the event to see what other industry leaders are working on.
National Oilwell Varco (NOV) has invested heavily in IoT solutions for their wells. NOV chose to develop most of the solution internally leveraging industrial PCs at the edge to run their own software. This required a significant investment in software development but that investment could easily be justified given the fact that machine downtime costs can exceed $1M per hour. The presenter showed two scenarios during the talk, the first involved outfitting a well site that allowed for local viewing of telemetry data and dashboards while streaming the same data back to a centralized historian. Local visibility was required to ensure the system was still available locally if the back-haul network was down.
Pipeline case study: https://www.nov.com/products/line-pipe-inspection-services
In the example case study, poor water quality at the well site was leading to clogs in cooling lines. As a result, NOV added pressure sensors to the legacy site to monitor input and output pressure at the cooling water pump. The data allowed National Oilwell Varco to implement a system maintenance process base on the real-time state of the machine rather than estimating a maintenance schedule based on prior system failures. The results included completely eliminating pump failures due to clogged lines and increased up-time due to a machine centered maintenance cycle.
The second case study highlighted a very expensive machine involved in high temp cleaning of well pipes. The impellers embedded in the machine operate in a very stressful environment and must be replaced periodically to ensure proper performance of the machine and process. Prior to the IoT project, the only way to evaluate the status of the impellers was to perform a visual inspection of the machine which involved taking the machine off-line for multiple hours. National Oilwell Varco was able to add vibration sensors to the machine and develop a process for determining the state of the impellers based on the vibration data. The results included reduced down time by eliminating visual inspection saving NOV millions of dollars annually per system.
Brose Group is the largest manufacturer of brush-less motors for car seats and doors. Brose is investing in MES solutions for their factories to eliminate paper based tracking of the manufacturing processes. Their core strategy is based on creating a platform agnostic system for data aggregation. Leveraging open standards like OPC-UA they have the ability to capture data from machines on the factory floor. For legacy machines that do not offer a standard data interface gateway like the Flexy 205, are required to convert the machine communications protocol to OPC-UA. This is an effective way to digitally transform a brown field site without disrupting current manufacturing options. Brose is still developing their system with the primary goals of increase efficacy, operational transparency and higher levels of trace-ability.
Brose products page: https://www.brose.com/us-en/products/
Boeing is working through a process of connecting all of their machines to improve overall efficacy and increase operation transparency. Boeing is leveraging MQTT and gateways to translate legacy machine data to an IT preferred communications protocol. Moving forward Boeing requires any machine develop for their manufacturing process to support a standard data communication protocol (MQTT or OPC-UA). The first example included leveraging machine learning to compare data from many metal fabrication machines executing the same manufacturing process. Boeing has been able to successfully aggregate data from all of the machines and then using AI compare the performance of each machine to one and other ultimately identifying machines that are under performing so they can be place on a maintenance plan.
First Line Analysis with Altizon