Industry 4.0
How To Present A Foolproof Business Case To Start Your Industry 4.0 Journey
How to convince your boss it's time to start your Industry 4.0 journey.
You're convinced you need to start your Industry 4.0 journey. You've also convinced key business stakeholders that the time is right. Here's where the hard (but rewarding) work begins.
The first roadblock you're likely to face is how to take those first steps on your Industry 4.0 journey. This article explores how to overcome this roadblock and shares a customer success story to inspire you to get started today.
A pilot project allows for the testing and refinement of Industry 4.0 technologies in a controlled and quantifiable way. It also allows for any roadblocks to be identified and resolved prior to technology implementation on a larger scale.
This is your proof of concept. As such, it will highlight potential roadblocks and inadequacies in the solution. The process of fault finding and improvement implementation during the course of the pilot project means it may run longer and cost more than originally planned. However, this extra spend is an investment in your operations as problems uncovered at the pilot stage are resolved prior to the implementation of a full-scale solution.
A manufacturing business quite likely already has some of the foundations laid. If the business has already deployed operational sensors on the production line, it’s possible these can be better utilised to deliver fresh benefits that weren’t initially considered. For example, a production line might include standard sequence sensors which are used to trigger a cylinder moving a load from point A to B and back. The sensors’ job is purely operational and not related to maintenance, but by using the sensors to measure the time the cylinder took to move back and forth, a maintenance manager could be alerted to potential problems. Monitoring the data that is being produced by sensors that were already installed would help avoid machine downtime and improve OEE rates. A set of operational sensors thus become part of a predictive maintenance solution.
Adding sensors to a production line used to be expensive and potentially disruptive due to the need to hard-wire them in. However, modern sensors are dramatically cheaper now and advances in technologies have made wireless sensors a logical option over their hard-wired counterparts. This combination offers plant managers a simpler solution that can add immense value at very little cost or machine downtime. By adding just one more sensor, production managers can greatly improve their uptime and quality of output. For example, a manufacturing business using steel as an input might identify that uptime and quality rates on a production line were being affected by the quality of the pressed steel going into the machinery at the start of the process. By adding a sensor to quality check the steel on the way in, the PLC could then accept or reject the steel before it entered the line, preventing sub-standard material from adversely wearing the machinery and improving quality KPIs at the same time.
Adding or updating PLCs can be a cost-effective way for businesses to get more value out of existing sensor installations on a production line. With the right PLCs in place, raw data capture and transformation can be automated thereby helping production managers to make better use of the resulting information. A common scenario for many plant managers is that their older PLC is not equipped to draw value from IIoT and AI sensing technologies. A cost-effective alternative to purchasing a modern PLC is integrating an edge solution and specific sensors in your facility. An edge solution coupled with sensors can achieve equivalent or superior results at a fraction of the cost of a standard PLC.
A large company located in China running multiple lines had no way of monitoring or reporting on overall efficiency or quality specifications of outputs. While expected to improve production statistics such as quality output and OEE, they had no way of measuring their progress. At the most granular level, the Plant Manager had no way of determining the amount of power or air consumed on each line, so could not ascertain the cost of production per part produced. While on the manufacturing floor, operators had no visibility or control over maintenance so were always ‘on the back foot’.
The Plant Manager seized the opportunity to utilise new technology on old lines, when two new lines were added.
Utilising an edge computer, specifically COSMOedge from Facteon, the team was able to capture the relevant data, send it to the Cloud-based COSMOline IIoT software, leading to real-time monitoring and resulting efficiency reports.
The client is still going through the internal onboarding process so specific KPIs are not yet available. But the indicative KPIs we recommend (which varies depending on the specific manufacturing environment, process, equipment and operator skills) are as follows: