Smart Industry 4.0 Solution

The Challenge/Opportunity

In today’s marketplace, customers are increasingly demanding customized products and services, and manufacturing and logistics companies must be able to quickly adapt to these changing demands. This requires a level of agility and flexibility that can be difficult to achieve without real-time data and insights into production and supply chain processes. Further, Certain manufacturing process involves complex data collection tracking over 75+ process variables per product per hour across multiple systems, which is complex and time-consuming task, particularly if the data collection is done manually. Thus, these challenges surrounding the manufacturing industry were identified by the and endeavored to develop an automated system that could automatically detect the process variables based on the product, effectively communicates and triggers alarms to the process department and effectively provide real time information for improvement and monitoring.

But, to develop an automatic complex system, the client had internal challenges regarding their talent and capabilities.

The Opportunity

The client had done due diligence on DSRC and understood that DSRC had supported various clients in developing automated complex systems efficiently using IoT based technologies. Reference checks were done with various client references and then the opportunity was provided to DSRC.

The Approach & Solution

Since the development involves tracking of various parameters at various time intervals for various products in the manufacturing process, the data recorded needs to be reviewed and analyzed and then needs to report to the stakeholders using various dashboard reporting tools. The architecture of the system involves receiving and recording data from various devices and sensors, machine logs and manual data entry by the workers. The system to be developed needs to provide real time monitoring of the collected data, and alert managers and workers if certain process variables fall outside of established thresholds or if other anomalies are detected.

Since the proposed system to be developed handles huge amount of data coming in from various sources and needs to be monitored at various frequencies and intervals, DSRC had deployed a team of data engineers and analysts to support with development of the system along with a large team of talented developers, test analysts, ETL developers and developers with experience in developing dashboard reporting tools.

DSRC developed the application in a record 5 months’ time, delivered and supported hosting the application on Cloud. For cloud deployment, DSRC used its cloud computing and SysOps team.

The developed application tracks about nearly 80 process variables by product for every hour across multiple systems like wet phase, Dryer, Bagger and more. Certain variables are recorded after every one hour and certain variables are recorded after every 6 hours, like a metal detector test. The application can monitor about 60 different products and can monitor and record different and similar set of variables from each of these products. The application uses various tools and techniques for data analysis, such as statistical process control (SPC), machine learning, and predictive analytics. The goal of data analysis is to identify patterns, trends, and anomalies in the production process and to use this information to optimize performance.

The system is developed with future scalability and can be integrated with other systems, such as manufacturing execution systems (MES), enterprise resource planning (ERP) systems, and supply chain management (SCM) systems. This is achieved with the development of robust interfaces and APIs to ensure that data is shared seamlessly between systems.