Did you know that you can decrease product defects, save time and cut costs in your factory with big data?
All the answers to your unique business lifestage questions
You have a lot on your plate – ensuring error-free production, monitoring the speed of the process and keeping expenditure low in your manufacturing business. “In each market, factory managers are under renewed pressure to optimise processes and lower costs,” says John Mills executive vice president of business development at Rideau Recognition Solutions. “Analytics tools could hold the key to finding areas of improvement.”
Related: Decoding the buzzword that’s known to you as ‘Big Data’
Two-thirds of companies that took part in an MIT Sloan survey claimed that using analytics gave them a competitive edge. Harnessing data provides a crucial boost your factory could benefit greatly from.
Consider the following benefits of big data in your factory:
1. Deliver real-time accuracy
The use of big data and advanced analytics, enables manufacturers to view product quality and delivery accuracy in real-time. This allows suppliers to accommodate time-sensitive orders. “After-the-fact analysis of big data captured from automation process helps identify opportunities for improved efficiency, velocity, and quality,” reports Intel on the effect of introducing the concept to its factories. It also assists Intel identify additional areas requiring automation.
The result is prioritising the quality measurement of metrics becomes the priority above solely measuring delivery schedule performance.
2. Profitably scale your operations
“Big data and advanced analytics are delivering the missing link that can unify daily production activity to the financial performance of a manufacturer,” says Mills. Senior management and production planners know how best to scale operations when equipped with knowledge of the machine level and whether the factory floor is running efficiently. Unifying daily production to financial metrics gives you a greater chance of scaling your operations more profitably.
Related: Off-site data storage
When analysing big data, Intel focuses on the following performance measures:
- Efficiency is measured by operational costs along with revenue, customer satisfaction and quality.
- Velocity is derived from lead time, amount of work in process and average completion rate per process.
- Quality and traceability are measured as critical aspects of overall efficiency.
3. Monitor and pre-empt maintenance
You cannot fix something you aren’t aware of, and that’s where sensors come in. But as manufacturers begin to look at producing more complex products, the need for an operating system to manage the sensors on board arises.
“These sensors report back activity and can send alerts for preventative maintenance,” explains a McKinsey report. Big data and analytics will make the level of recommendations contextual for the first time so customers can get greater value.”
General Electric for example, has already put this into place with its jet engines and drilling platforms. “Companies that successfully build up their capabilities in conducting quantitative assessments can set themselves far apart from competitors,” the report concludes.
According to McKinsey, the critical first step for manufacturers that want to use advanced analytics to improve yield is to consider how much data the company has at its disposal. Most companies collect vast troves of process data but typically use them only for tracking purposes, not as a basis for improving operations.