The manufacturing and consumer market are getting more competitive every day with a lot of options for the buyer available on the shelf or just a few clicks away. Brand differentiation is important to remain top of mind for buying decisions. For example, in the food industry, more than 80% of food consumers consider the impact of how and where food was produced when making a purchase. Trends show that consumers want to know more than just the nutritional information - they want to know the food’s origin, when it was grown, and how. What are the demands in your industry? How is your company innovating to stay ahead of the curve?
This article focuses on examples from the food industry, but the lessons learned can be applied to supply chains in other industries. For example, the bar is rising for safety, quality and traceability in other markets like pharma, medical devices, automotive and aerospace. Companies are moving beyond regulatory compliance in these industries. They want to get ahead of customer demands and make sure their supply chain can meet these data and traceability requirements.
Driven by recent sustainability awareness efforts, consumers think it’s important for food to be produced in a sustainable way. In fact, many people claim they would switch brands following a recall. Consumers want more details and visibility about the food they consume in order to make informed decisions.
The pressure is growing on manufacturers to institute product recalls as quickly as possible. The traceability of contamination is, however, a complicated matter, as several factors such as microbial impurities, labeling and packaging errors, contamination by metals, plastic, glass or potentially dangerous substances such as machine oil or biohazards must be taken into consideration. Therefore, processes must be put into place to identify and eliminate sources of error.
Sensor technologies contribute greatly to this effort. There are many varieties of intelligent identification systems which enable better traceability. For instance, radio frequency identification (RFID) labeling tracks crops right from harvesting in order to be able to trace the origins of the cargo. There are also other systems that allow systematic and efficient data tracking from raw material to end product.
In order to meet customer demands, meet traceability requirements for labels like “organic” and “gluten-free”, and comply with regulations that includes the Food Safety Modernization Act and the European Union’s General Food Law, food manufacturers are turning to technology solutions to modernize the supply chain communication, coordination, and data flow.
Manufacturers are implementing “traceback” initiatives with data exchanges in their supply chain to trace a food product from the retail shelf back to the source all the way back to the farm or fishery. As the food supply chain becomes more globalized it becomes a complex web. Weaved through this web are varied state, Federal and international regulations and standards that food companies must adhere to. Their ability to ascertain the origin of products and ingredients from the farm through food processing to retail, foodservice and the consumer, depends upon effective food traceability systems.
In legacy processes, tracing food across the supply chain takes days, if not weeks, as companies struggle to track a mix of digital and paper-based food data documentation across a complex and growing network of suppliers and distributors. These practices of storing compliance data either on paper or in centralized databases are susceptible to inaccuracies, hacking, and intentional errors motivated by corruption. Regulators are now demanding state-of-the-art practices and modern technologies to ensure food safety. Because of the complexity of these supply chains and the variety of stakeholders, blockchain is one of the technologies being used for these data exchanges.
A shared digital food supply chain powered by blockchain enables full transparency by digitizing transaction records and storing them in a decentralized and immutable manner, eliminating opportunity for fraud across the food chain.
Food tracing (aka food trust) systems allow corrective actions to be implemented when a potential safety or security problem is identified. A key goal of food traceability is to be able to quickly isolate and prevent contaminated products from reaching consumers and from causing risks to public health. All food businesses including producers, retailers and importers must be able to trace products through the food chain.
Food trust (or provenance) is an important issue not just for consumers, but it is for the large players in the industry as well (e.g. Walmart, Albertsons and Golden State Foods) who are looking at innovative approaches to provide better traceability for food products that they supply to consumers. This paper focuses on the usage of IoT data, in combination with Blockchain technology, as one approach to solving this problem.
The following is an example of how data exchanges and blockchain technology are being threaded together to provide a better, more transparent, means of tracking the movement of food through the supply chain. The example uses GS1 EPCIS standards in the food supply chain and is based on a project involving grocery chains and blockchain technology. [1] Examples of the project goals include:
- Foods, especially cold or frozen, must be maintained within a specified temperature range during shipment.
- There might be contractual terms around shipment times and delays.
- The food shipped by the manufacturer must be the same as the food received by the retailer.
As can be seen in Figure 1 below, the participants involved in this type of supply chain include:
- Farms – may, or may not, have the ability to tag the “product” in some way so it can be tracked with IoT. They may, or may not, also have the ability to initiate the shipping process from an EPCIS perspective.
- Manufacturers – package the goods and create a shipment against a schedule or customer orders.
- Distribution Centers – manages the logistics of the shipments and intermediate storage, combining orders as needed to optimize usage of transportation and shipment times.
- Transporters – Trucks, Rail, Ships, Air – move shipments as directed by the Distribution Center.
- Stores – the customer in this use case.
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Figure
1: Food supply chain
data flow example
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Systems exist already to track this type of shipment based on the GS1/EPCIS standards. What those systems do well is to capture the business events (as EPCIS events) related to the shipment, typically in a centralized server managed by one of the participants in the Supply Chain Network (this could be a large customer (e.g. Walmart, Albertsons), or it could be a large manufacturer (e.g. Tyson Foods). Other participants may have their own systems as well that they are updating given EPCIS/GS1 (or EDI) events.
The problems with the traditional approach include the following:
- Either one big player with a centralized system owns all the tracking information, or, the individual players have tracking systems which must be synchronized.
- Typically, IoT information (such as temperature readings) are not integrated with the business events (i.e. EPCIS events).
- There is not a “trusted, single source of truth” for all of the information related to the shipment.
In order to address these issues, a couple of “twists” to the standard GS1/EPCIS approach were introduced to tracking shipments such as this.
- IoT events pertaining to contractual issues governing the shipment (such as temperature, or perhaps “shock” (package dropped)) are captured and are combined with the EPCIS events to provide additional context to the shipment process records.
- Blockchain is introduced to address the problem of having a single, trusted source of information about the shipment, which is equally available to all participants in the supply chain process.
This is one example of how new technologies like blockchain are being used to achieve new levels of connectivity in the Smart Manufacturing ecosystem. MESA International is covering a broad spectrum of examples of Smart Manufacturing in multiple dimensions including digital thread, smart factory and value chain. For more examples and more information on these dimensions visit the MESA Smart Manufacturing resource page at MESA.org [3], and view the recorded webcast: [4] Three Dimensions Converge on Smart Manufacturing – IIoT, Digital Thread, Value Chain. We also encourage you to become MESA members and read MESA White Paper #59: Three Functional Dimensions Converge On Smart Manufacturing. [5]
References:
[1] Albertsons Joins IBM Food Trust Blockchain Network To Track Romaine Lettuce From Farm To Store, Forbes, 2019
[2] Guilda Javaheri, Chief Technology Officer of Golden State Foods, describing the importance of collaboration in bringing their new blockchain solution to life, Youtube, April, 2019.
[3] Smart Manufacturing Explained (through multiple articles and videos), MESA International
[4] Recorded Webcast: Three Dimensions Converge on Smart Manufacturing – IIoT, Digital Thread, Value Chain, MESA International, 2019
[5] MESA White Paper #59: Three Functional Dimensions Converge On Smart Manufacturing, MESA International, 2019
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