Big data analytics is already part of the packaging industry, but is about to get a whole lot more important, according to the latest white paper from the Packaging Machinery Manufacturers Institute (PMMI) in the US, which dissects big data and examines how manufacturers can use it to transform their businesses, looking at the opportunities, the challenges, and the ROI.

The white paper says that while manufacturing sectors such as automotive, electronics and aerospace are already employing big data analytics, food and beverage processing was somewhat reticent to take up the technology. This changed in recent years, however, and large food and beverage processing companies are now making use of big data analytics for a number of applications. These include keeping an eye on machinery, identifying mechanical problems and fixing them before the equipment fails; improving measurement, product sorting and food safety; allowing product customisation; and creating new recipes.

The PMMI's white paper says that food and beverage manufacturers will be able to significantly ramp up there implementation of big data analytics into their processes, to solve a variety of different issues and pain points, including increased demand for customisable products, and the need to improve quality monitoring. These solutions will identify faults early in the production process, thus increasing productivity, and reducing wastage, so minimising cost. The white paper says that ultimately big data will lead to the entire process being automated to eliminate human error.

Manufacturers are facing many challenges that are motivating them to introduce or expand big data solutions.. These challenges include the need for increased efficiency, reduced downtime, quality management, flexibility and cost savings. To address these challenges, manufacturers are leveraging smart technologies that include networking/connectivity, the cloud/edge data storage, as well as remote monitoring.

Significant investments are often needed to successfully pursue big-data programs. These involve not only infrastructure and hardware, but the necessary software to collect, aggregate and analyse the data for human consumption; as well as this, staff who use these tools will usually require data science training to make sense of what they find. Employee buy-in can be an issue, with people often hesitant to embrace new technologies they don’t understand.

While the use of data in manufacturing is not new, the potential shift in scale, volume and frequency of data collection is. The sheer volume of data can also present challenges, with some companies reporting that they have gone from collecting data every three months to collecting it every five seconds, putting a strain on analysts and resulting in a high number of alarms for technicians to deal with. In addition, all that data has to be stored somewhere, which raises issues around cloud usage and security: many manufacturers are reluctant to trust third-party cloud hosting services with their valuable information.

To alleviate these challenges, businesses can take simple security measures such as encrypting data while transferring it to and from the cloud, limiting the risk of theft. Alarms can be prioritised in order of urgency to reduce the demand on technicians and analysts, and employees can be guided by experienced champions, who can educate them in the use of the new technologies required.

For businesses looking to implement big data analytics into their operations, PMMI recommends first looking at these six steps: specify the problem that needs solving; define what success will mean for the project; start small with proof of concept; obtain senior support with a vision of how the technologies will be used; share responsibility with both IT and operational technology (OT) teams; and get your support staff involved in the project.

This report summary was brought to you by the Australian Packaging & Processing Machinery Association (APPMA), an alliance partner of the PMMI. Find out more about APPMA here 

The PMMI white paper, How to Utilise Big Data to Enhance Manufacturing Processes, can be accessed here 

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