In controlling your processes, the use of KPIs and the subsequent reporting on them, are key. However, in the pipe blasting and coating business, the amount of data that can actually be used for analysis is generally limited. The same goes for functionalities of the average PLC. Hence, many production sites are suffering from control issues. To end the suffering, we have developed the Selmers Plant Management System.
Lack of uniformity
Data derived from the equipment itself are commonly limited to parameters such as energy usage, motor performance, output ratios and downtime. This probably won’t come to you as a surprise as most of us know that the use of IT technology in heavy industries is lagging behind the level of automation in many other industries. In a, often desperate, attempt to disclose (and report on) more relevant data, we often see pipe blasting and coating facilities improvising and crafting their own ‘solution’. Lacking uniformity, these solutions are obviously useless for benchmarking purposes for example.
Online reporting
This is just one of the reasons why all data in our own solution are highly structured and presented in a uniform way. Unlike unstructured data, this also allows them to be used for further analysis by means of BI software. On top of that, our platform allows for both on-site and remote reporting, while reports can be tailored to the specific needs of either individuals or departments. “If only we knew about this solution earlier”, a foreign pipe coating company recently must have thought. “Being on the verge of going out of business, they recruited two of our colleagues for no less than two years just to map and measure all KPIs on a daily basis.”
Smart Mobile Warehouse
Getting the site back on track also included improving preventive maintenance. Part of this was achieved by taking key supply parts into stock using our Smart Mobile Warehouse. This facility is situated at the customer’s site and uses product identification technology. It contains a pre-agreed inventory of strategic parts, consumables, and assemblies that are automatically monitored and ordered using a radar detection system. Being familiar with Internet of Things, we have already prepared our platform for more IoT applications to be integrated. In doing so, we are paving the way for further, near-future improvements using Artificial Intelligence and Machine Learning. Thus making our line of business even more exciting than it already is!
