Production Data Management System for Diatomaceous Earth Processing

Project Drive

A leading diatomaceous earth processing facility was storing its production data in Excel spreadsheets. The long-term effects of this method led to a proliferation of spreadsheets on their servers, making it difficult to efficiently access necessary information. The best remedy for this problem was to move to a web-based solution. This approach provided a centralized database to store the data and an interface for authorized users to enter, edit, and view the data.

Solution

Corso Systems staff worked with a large diatomaceous earth processing facility to implement a web-based system to store and analyze its production data. We used the client's existing paper and Excel-based tools to develop a database schema for the data. With the database in place, we developed the web-based front end for operators to enter new data and access existing records. In addition to data entry forms, the interface included automated reporting functionality, allowing users to select a date-range and/or specific process areas to view production data. The system generates nightly reports and automatically sends them to key personnel. In addition to tabular views of the data, the system includes charts and tables for tracking downtime and product loss reasons for a range of dates, as well as process OEE. The system also includes the ability to automatically gather and store data from the process historian.

Benefits

  • Centralized database for production data

  • Advanced analysis tools for production losses, downtime, and OEE data

  • Automated reports sent out to key personnel on a regular basis

  • Reduced overhead costs

  • Increased data utilization

  • Increased productivity

Project Details

Industry: Mining

Location: Lovelock, NV

Services: Web-based tools, Technology Migration

Technology

  • ASP.NET

  • ASP.NET MVC

  • FactoryTalk Historian

  • SQL Server

  • jQuery

  • Javascript

Focus

  • Centralize production data

  • Decrease data management overhead

  • Optimize business processes

  • Understand existing processes

  • Develop web-based system

  • Implement system and train personnel on its operation

  • Increase value of business data by integrating it with process data

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