What is Big Data Analytics?
The industrial internet of things (IIoT) is changing the way we live and work, and extracting maximum value requires a big data approach.
The industrial internet of things (IIoT) is an exciting outcome of the digital revolution that is changing the way we live and work. Many organizations already focus on how to benefit from it, but extracting maximum value requires a big data approach.
Operational Savings and Revenue Opportunities
- The benefits of big data are clear to executives.
- Nearly two-thirds believe big data can enable well-informed decision in real-time
Through the IIoT, operations technology and information technology will blend together and become more intelligent through the use of sensors, analytics and machine applications – a development that will share and create even more data. The insights gleaned from this big data and new types of data can bring many benefits for businesses, including operational savings and revenue opportunities.
For example, research has indicated that predictive maintenance can generate savings of up to 12% over scheduled repairs, leading to a 30% reduction in maintenance costs and a 70% cut in downtime from equipment breakdowns. For a manufacturing plant or a transport company, achieving these results from data-driven decisions can add up to significant operational improvements and savings opportunities.
Blue Ocean's Approach - Big Data Analytics
The key challenge for organizations is to drive actionable insights and, ultimately, incremental value from data generated by IIoT. To do so, organizations must think about how they collect, store and analyze that data.
The good news is that setting up a big data platform to leverage IIoT can be done incrementally without needing a big up-front investment.
We recommends that organisations begin implementing their big data strategy in an agile way with a small proof of concept. This approach will show them which data combinations generate the most value before they scale into a broader enterprise solution. Cloud-based approaches are also becoming more common because they provide greater flexibility to scale up and down as the business need evolves.
Example of Big Data Analytics Dashboard for OEE Monitoring
Below system captures machine data from the source. After data compilation and making use of big data processing technology, it able to provide management with real time information on what happening in the shop floor. Quick response and actions can generate significant cost saving and revenue opportunities.
Example of Big Data Analytics for Process Study
Below data is captured through real time in process measurement system. Through big data analytics technology, it enables process and quality engineers to perform real time process troubleshooting and quality analysis for quality improvement and process optimization.
Variability Chart for DIAMETER
