White Paper. Winning at Process Control and Monitoring with Big Data

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1 White Paper Winning at Process Control and Monitoring with Big Data

2 Not long ago, it was mostly large multinational food processors with deep pockets and technical sophistication that could adopt advanced process control and monitoring systems for the purpose of creating competitive advantages. Now, as the cost of these systems falls and ease of use rises, even the smallest regional processors are rapidly joining the game and leveling the playing field. The race is on to utilize systems to collect, analyze and share data in ways that improve food safety and product quality while increasing efficiencies to reduce line operating costs and maximize yields. The goal is to tap into bigger data sets that can yield the next-level of insights for continuing to enhance processing operations. This white paper will explore how digital data, powered by IIoT (the Industrial Internet of Things) and Industry 4.0 methodologies, is transforming the food supply chain from growers to retailers, with a close look at how food processors of all sizes can best utilize these tools. The Supply Chain At each step within the supply chain, the ability to leverage advanced sensor technologies and smart systems to collect, analyze and share data promises significant rewards. Growers can monitor fields and environmental conditions to manage pests, adjust nutrients and schedule planting and harvesting in order to produce larger and higher quality crops. Food storage facilities control environmental conditions to ensure optimal storage and reduce spoilage, maximizing food safety and product quality. Food processors leverage smart technologies at multiple points within their operations to improve production efficiencies, food safety, product quality and process yields. Distributors automate trackand-trace functions to reduce inventory and better secure their portion of the supply chain. Retailers analyze purchasing patterns to quickly identify changing consumer preferences and adjust their product offerings to reduce waste and improve profitability. Finally, even the end consumer is beginning to have access to tools and information at the point of purchase, which allow a better understand of the origin and process history of the products they are buying. Industry 4.0 allows aggregating, in the cloud, the data collected at each step within the supply chain, creating an integrated end-to-end information exchange from farm to fork. For example, a digital sorter at a food processing plant may be collecting data about the color, size, shape, structural properties and chemical composition of its products during the production process. This information can be shared with raw material suppliers, informing them of trends that allow the grower to take corrective action to improve future quality. Key Technology, Inc. 2

3 Or, to take a page from the track-and-trace initiatives required of pharmaceutical manufacturers serialization and aggregation solutions could be adopted by food processors to offer greater transparency and security. Associating every product batch to a unique code and connecting the data to a multi-tenant cloud solution enables seamless two-way communication between the food processor and their customers. Such efforts can help industry players respond more quickly to food safety and product quality problems when they occur, allowing them to speed resolution and promptly isolate the problem to limit exposure. Supply chain traceability also has marketing value, as consumers are increasingly interested to know the origin and condition of their food. Consumers can scan the barcode on a product package with their smartphone to learn more of the product s provenance, informing them of growing conditions, sustainability and more. Food Processing While the vision of fully integrating the entire supply chain remains somewhat futuristic today, the data revolution is well underway within food processing companies of all shapes and sizes around the world. The benefits being achieved depend on the nature and extent of associated technology adoption. Data from a smart machine can improve the system s operations, conducting selfdiagnostics tasks, sending smart alarms, performing auto-learning functions and more. Integrating smart equipment on a line enables data from one system to improve other systems along the same production line. In between machines, unique sensors on the line, such as at the outfeed of a freezer or prior to packaging, can share the data they collect to monitor and control a wide variety of process parameters. Beyond individual machines and line integration, delivering data to the enterprise level empowers the large-scale analysis of big data. The ease of harnessing large amounts of valuable data is rapidly improving and, with larger data sets, comes the opportunity to develop more valuable insights and actionable information. To be an effective smart device within the Industry 4.0 framework, flexibility to support a variety of data formats and connectivity protocols is essential. Proprietary formats are unlikely to scale. Key Technology, Inc. 3

4 Today s sophisticated equipment often features advanced software that enables universal connectivity via OPC-compliant infrastructure. Many modern systems support integration with virtually any factory automation systems from any manufacturer, in addition to Modbus and Ethernet/IP devices and the creation of CSV and database files. Whether the data is collected off-line, on the plant floor or remotely via connections to the factory s MES and SCADA systems, processors that can collect, analyze and share big data are empowered to make more informed decisions. Tapping Digital Sorters Digital sorters, which remove defective products and foreign material on many processing lines, contain enormously powerful sensors and are ideally suited to contribute to the digital data revolution. This is because they continually inspect 100 percent of what is flowing through the line and are able to recognize each object s color, size, shape, structural properties and/ or chemical composition, depending on the sorter s sensors. Digital sorters feature powerful computers that can process large volumes of data and are easily connected to the processor s enterprise. Through its Information Analytics capabilities, a sorter can collect real-time data and generate reports about the sorting process and every product and object on the line, whether the data is used to perform the system s sorting function or not. The data can be harnessed to optimize processes upstream and downstream of the sorter, in addition to improving the sorter s own performance. Around the world, food processors of all sizes are harvesting data from their digital sorters to help them improve their operations. There are almost as many examples as there are processors: A sorter inspecting raw product at receiving can analyze the quality of incoming product by lot or by supplier, enabling the processor to develop a payment scheme that rewards higher quality. A sorter located after a transformational process can collect data used to control the upstream process. For example, a potato sorter after the peeler can detect remaining peel and control the upstream peeler in real time to optimize its operation. A sorter can control a downstream process too. In the case of a critical foreign material (FM) event, such as the sorter finding a piece of glass in the product stream, the sorter can actuate a downstream gate so part of the product flow is diverted, supplementing the security measure to ensure the FM removal. Key Technology, Inc. 4

5 Or it can offer predictive analysis, issuing a smart alarm as soon as certain conditions of interest begin trending in a problematic direction. For example, a smart sorter will recognize that a sensor channel level is trending over time in a direction that is indicative of a hardware issue, such as a laser source or receiver failure, and send an alert so the situation can be corrected early. At the end of the processing line, immediately prior to packaging, a sorter will ensure the product is free of contaminants and can collect valuable data about final product quality to help manage upstream processes and strengthen Quality Control (QC) record-keeping or even displace QC processes that used to be conducted off-line and on smaller, less statistically significant samples. For processors that operate multiple sorters on different lines or production facilities, data can be compared across systems to help managers optimize performance and achieve operational consistency. New aspects of Information Analytics have made it easier than ever to use a digital sorter to collect data. Each processor can define specific data categories of interest to them. For example, a processor might wish to see information about the distribution of their product s length grade or trends about the occurrence of various defect types over time. A custom-defined dashboard can be viewed on the sorter s UI as well as remotely on a connected PC or smart mobile device. Key Technology, Inc. 5

6 Challenges & Solutions To maximize the rewards of leveraging big data for the purpose of process control and monitoring, these three challenges must be addressed: It s necessary to select the relevant data sets that offer insights that are most impactful to the operation, selecting from the enormous volume of data that could be collected. Data security must be effectively managed. When integrating technology from different suppliers, whether connecting various systems within one facility or linking constituents along the supply chain, collaboration is essential or progress will be slow and ineffective. The fastest and easiest way to address these challenges and the most effective way to achieve the best results is to partner with qualified suppliers that are ready to lend their expertise. Working with partners and integrators that know your process, understand your business and have deep experience with Industry 4.0 protocols is invaluable. Proprietary data formats and processes should be avoided in favor of systems that offer standard formats and connectivity protocols. Conclusion Today, food processors of all sizes are collecting, analyzing and sharing digital data across their enterprises to monitor and control processes. The rewards elevating food safety, optimizing product quality, improving production efficiencies and increasing yields come from zeroing in on information sets that can be turned into useful, actionable knowledge. The next wave will come from fuller data integration throughout the food supply chain, from field to fork, with each constituent collaborating to share information seamlessly and safely beyond the walls of their entity to benefit the overall process. The technology exists and the industry needs it to achieve its objectives. Published by: Key Technology, Inc. 150 Avery Street Walla Walla, WA T E product.info@key.net Key Technology, Inc. 6