Problem Statement
With quality standards and deadlines becoming more stringent for industrial projects, keeping complete track of the weld quality, man and machine availability, and resource utilization was becoming an increasingly challenging task for one of our customer.
They found out that their current monitoring and reporting setup wasn’t efficient enough and required a lot of overhead expenditure.
Solution
To address this challenge, we developed an end-to-end welding IoT solution for their GMAW, SAW, and TIG welding machines called the Weld Insight.
We received an order for five machines initially. Access to their existing machine program and HMI was not possible due to restricted access. As a result, we decided to build a parallel system to get the necessary inputs and data like current, voltage, energy consumption, wire consumption, speed, etc. for our analytics.
Architecture
The PLC-HMI panel-based system was coupled with an encoder wheel assembly to measure wire consumption and an energy meter to capture energy consumed by the machine. We attached our ZiG IoT Gateway to this system to push the computed data to their on-premise server. We also developed a backend application and a responsive web dashboard to showcase the KPIs to the stakeholders from the analytics.
Key Features
- No-hassle Audits - Wow your auditors with the modern method of tracking your welds without losing papers.
- Improved Production - Record weld parameters, identify reasons for down time, and improve machine planning.
- Easy Reporting - Quantified and graphical data for cost analysis and decision making in one place.
- Improved Quality - Study changes in trends to identify weld issues, weld efficiency, and improve quality.
- Detailed Analysis - Examine the consumption of energy, raw materials, and resources.
Impact
The entire project took 2 months to develop and another 1 month for testing and deployment.
After the project deployment, within a period of 6 months they were able to address their previous weld quality concerns by studying the trends of welding parameters. It also helped them monitor their operators, machines, and raw materials, which in turn resulted in improved efficiency by better planning from the real-time data captured at all times.
We have received repeat orders for the same solution and have completed deployments for 40+ machines in different industries.
