Enhancing Linamar’s big data analytics capability for continuous improvement in production

Digital transformation is a global trend for many industry sectors, and it is extremely important for manufacturing companies to avoid being excluded from the global digital supply chain. Linamar which operates 60 advanced manufacturing facilities worldwide, as a leader in manufacturing solutions, has been investing in this new trend with the ultimate goal of achieving data-informed continuous improvement in production since 2010. A large volume of machine-related big data has been collected across its global facilities using sensors and gauges. Linamar and the University of Guelph have previously formed a partnership to develop a pilot development environment that was able to extract data from Linamar’s distributed database and conduct some preliminary analysis such as machine utilization and production constraints. However, there are several challenges that need to be further addressed to fully maximize the value of such industry data, including inconsistency in data description, lack of data quality governing scheme, deficiency in machine performance metrics, and low efficiency in data analysis. As such, this proposed project will build on the pilot development environment and enrich its functionality by focusing on improving data quality and enhancing data analytic capacity.

Faculty Supervisor:

Sheng Yang;Ayesha Ali

Student:

Partner:

Linamar Innovation Hub Inc.

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Guelph

Program: