Exploring Blockchain Projects in Food Supply Chain Management
This is a research part of the Food traceability Fund11 proposal milestone 1.
Food Traceability by Cardano Proposal funded Project Catalyst Fund 11
Exploring Blockchain Projects in Food Supply Chain Management: Capabilities and Limitations in Complex Systems.
Cristian Rojas
Industrial Engineer, Latam Cardano Community and Intersect MBO Member , Project Catalyst Proposer crjarove@gmail.com
Abstract:Supply chains have transformed into dynamic, interconnected networks, making it more challenging to achieve comprehensive traceability of products and their associated events. Blockchain technology, with its ability to provide a secure, transparent, and immutable system without needing a trusted intermediary, shows significant promise for enabling end-to-end traceability in these complex, multi-tiered supply networks.This research article reviews and analyzes blockchain projects in food supply chain management. It examines the ability of these projects to map highly complex supply chains with objects undergoing compositional changes. Additionally, the article identifies the limitations of these solutions when applied to dynamic, interconnected supply chains involving complex objects.
Keywords: blockchain, traceability, EPCIS, Supply chain management, Transparency, Complex supply chains, tokenization
1.Introduction:
The food supply chain is a critical component of the global economy, ensuring the safe and efficient delivery of food from producers to consumers. However, it faces numerous challenges, including traceability, transparency, and food safety. Blockchain technology, known for its decentralized and immutable ledger system, offers promising solutions to these issues. This article explores various applications of blockchain technology in food supply chain management and evaluates its effectiveness in managing complex supply chains characterized by objects experiencing compositional changes.
The concept of traceability and the implementation of traceability systems began in food supply chains and have since expanded to other industries. Olsen and Borit describe traceability as "the ability to access any or all information related to a given item throughout its entire lifecycle through recorded identifications" [1]. The GS1 Global Traceability Standard indicates that traceability information can include details about the origin of materials and parts, processing history, distribution and location.
Interconnected traceability systems track objects by documenting their events within the supply chain [2]. This event-based tracking method is part of the discrete mapping domain, which records event data at specific milestones. In contrast, continuous mapping collects data at regular time intervals. While discrete mapping is more commonly used, continuous mapping is mainly applied in specialized tracking solutions, like monitoring humidity levels in food supply chains[3].
The GS1 Global Traceability Standard specifies basic requirements for systems to identify objects, the standard distinguishes between physical and digital objects [4]. Based on this international standard, this paper uses the following definitions:
Physical objects: These are tangible items involved in the physical handling stages of a business process that spans one or more organizations. Examples include products, items, and physical documents, but specifically exclude human individuals.
Digital objects: These are intangible items involved in business processes across one or more organizations. Examples include digital trade items, digital documents, and electronic certificates.
To achieve traceability of objects, it is necessary to map data related to supply chain events, also known as object-related 'visibility events'. An object-related supply chain event is defined as "the record of the completion of a specific business process step acting upon one or more objects". The Electronic Product Code Information Services (EPCIS) standard, which is the most commonly used standard in industrial traceability systems, identifies key supply chain events: object creation and deletion, object aggregation and disaggregation, object transformation, and object transaction events [4].
Object event: Links objects to their identifiers (IDs) at a system level, allowing for the creation or deletion of objects. Deleted objects are no longer recognized in the system for future events.
Aggregation/disaggregation event: Creates a new identifiable entity containing a set of objects, which can later be disaggregated, making the objects independent again.
Transformation event: Consumes objects as inputs and produces new objects, allowing them to transform into different objects without changing their modular composition.
Transaction event: Associates or disassociates objects with business transactions, facilitating the mapping of ownership changes.
Growing demands for greater supply chain visibility and transparency have driven companies to intensify their efforts to map their supply chains. Despite this, it is still common for companies to only have visibility of their direct suppliers and customers, known as the 'one step up-one step down model,' resulting in limited overall knowledge of their supply chains [5].
To address this, companies adopted cumulative traceability, where each party stores traceability data centrally and forwards it along with the product flow. This method doesn't rely on a single central system but poses challenges for downstream parties managing large data volumes. To tackle these issues, the 'Plattform Industrie 4.0' initiative has proposed the Asset Administration Shell (AAS), a standardized digital representation of assets that aims to facilitate interoperability and streamline data exchange between companies in the value chain [6].
The AAS's advantage of not requiring a central system also leads to weaknesses in traceability. Without central oversight, compliance with standardized formats isn't monitored, increasing semantic complexity and data inconsistencies. Additionally, the absence of a central entity to ensure globally unique identifiers for objects and events further exacerbates these inconsistencies. Consequently, in large and complex supply chains, these issues can create big data problems rather than enhancing object traceability.
In 2016, Abeyratne and Monfared proposed using blockchain technology to solve end-to-end traceability issues in manufacturing supply chains [7]. Introduced by Satoshi Nakamoto in 2008, blockchain is the most well-known form of distributed ledger technology (DLT). DLT is a multi-party system where participants agree on shared data's validity without a central coordinator. The key difference between blockchain and other DLTs is how data is stored: blockchain records data in immutable "blocks" that form a continuous "chain," preventing deletion or modification of past information.
Blockchain technology stands out as a potential solution for achieving end-to-end traceability in complex supply networks. Its ability to create a secure, transparent, and unchangeable system, without relying on a trusted third party, makes it an attractive option.
Various blockchain-based traceability solutions have emerged, positioning blockchain as possibly the most promising technology for traceability services in supply chain networks. However, the current landscape suggests that each traceability issue demands a unique architecture design and blockchain platform. Despite the adoption of blockchain-based solutions, many architectures, especially in sectors like food and medical supply chains, have simplistic designs that only track single objects and fail to cover all supply chain events outlined by EPCIS.
Therefore, this research aims to answer the following research question (RQ):
What are the limitations of existing blockchain-based traceability solutions described in the literature?
2.Research Methodology
This research employs a systematic review of existing blockchain projects, including peer-reviewed articles, case studies, and industry reports, focusing on their application in food supply chain management. The review aims to evaluate these projects' capabilities in mapping complex supply chains and understand their limitations in dynamic and interconnected environments.
3.Description of the identified projects, how they approach supply chain mapping and a list of the limitations.
3.1 ProductChain: Is a permissioned blockchain framework designed for the food supply chain. It ensures transparency by allowing only authorized entities access and governance.
With a sharded, three-tiered architecture, it scales efficiently and maintains data integrity. The framework includes a defined transaction vocabulary and access rights to manage data securely. It protects trade flows' confidentiality while providing transparency to consumers. ProductChain tracks complex objects by assigning unique identifiers, recording transformations, and adhering to industry standards. Overall, it provides a reliable solution for tracing food products from farm to fork, addressing issues of mislabeling and handling.[8].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Sensor Data Integration:Incomplete integration of sensor data logging.
Disconnected Product Ledger: Vulnerability to missing intermediate transactions.
Scalability Challenges: Potential issues in managing highly dynamic and interconnected supply chains.
Complex Transformations: Difficulty in tracing products through multiple, complex transformations.
Governance and Consensus:Challenges in maintaining fair and effective governance among diverse participants.
3.2 Bruschetta: is a blockchain-based framework designed for the traceability and certification of Extra Virgin Olive Oil (EVOO). The system aims to provide a tamper-proof history of EVOO from plantation to shops, ensuring consumers can verify the product's provenance and quality. By leveraging Internet of Things (IoT) technologies, BRUSCHETTA interconnects sensors dedicated to quality control, allowing them to operate on the blockchain. This ensures the integrity and transparency of the entire production process, from farming to transportation.
BRUSCHETTA uses Hyperledger Fabric, a permissioned blockchain, to create an immutable record of the EVOO production process, integrating IoT sensors for real-time data collection at various stages such as farming, harvesting, and transportation. It adheres to European food traceability standards, ensuring compliance and consumer trust. The system includes a dynamic auto-tuning mechanism to optimize performance under varying transaction loads, and it allows consumers to access the tamper-proof product history via smartphones, ensuring transparency and authenticity verification [9].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
IoT Reliability: Dependence on IoT sensor accuracy.
Complex Supply Chain Mapping: Difficulty in documenting every step.
Implementation Cost: Expense of IoT and blockchain setup.
Interoperability Issues: Integration with existing systems.
Limited Applicability: Narrow focus on EVOO certification.
3.3 The blockchain-based safety management system specifically designed for the grain supply chain. This system aims to address issues such as data tampering, hazardous-material information management, isolated information silos, and low traceability efficiency.
The system uses Hyperledger Fabric blockchain to ensure secure, tamper-proof data management throughout the grain supply chain. It employs a multimode storage mechanism for efficient data handling and customized smart contracts to automate processes and manage hazard information. By capturing detailed information at each stage, the system provides comprehensive traceability of grain products. It facilitates real-time information sharing among all participants, ensuring data security, reliability, and overcoming information silos. Additionally, the system offers tools for hazard assessment, prediction, and early warning to mitigate risks [10].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Data Credibility: Ensuring trusted data collection.
Scalability Issues: Managing large data volumes.
Real-Time Processing: Ensuring timely data validation.
System Integration: Complex integration with existing systems.
IoT Reliability: Dependence on potentially unreliable IoT data.
3.4 The blockchain–IoT-based food traceability system (BIFTS):designed to manage and certify the entire lifecycle of perishable food. This system integrates blockchain technology with IoT devices and fuzzy logic to ensure accurate, reliable, and efficient traceability, particularly in the context of perishable food e-commerce. BIFTS aims to enhance system reliability, scalability, and information accuracy while addressing the unique challenges of managing perishable goods, such as quality deterioration and environmental sensitivity.
BIFTS uses a lightweight and vaporized blockchain optimized for efficiency and storage, integrating a novel PoSCS consensus mechanism that considers shipment transit time, stakeholder assessment, and shipment volume. IoT devices are strategically deployed across the supply chain to collect real-time data on environmental conditions and product status, with this data managed in a cloud database and recorded on the blockchain for immutable traceability. Fuzzy logic algorithms evaluate food quality decay and adjust shelf life, providing up-to-date quality information to consumers. Designed for scalability, BIFTS supports SMEs and e-commerce, ensuring comprehensive, end-to-end traceability and compliance with industry standards [11].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
IoT Reliability: Potential sensor accuracy issues.
Scalability: Handling large, dynamic supply chains.
Real-Time Processing: Ensuring timely data validation.
Complex Mapping: Documenting complex transformations.
High Costs: Deploying and maintaining infrastructure.
3.5 A Platform-independent, Generic-purpose, and Blockchain-based Supply Chain Tracking: The solution is a blockchain-based Supply Chain Tracking (SCT) system implemented as a decentralized application (Dapp) on the Ethereum blockchain. This system is designed to be platform-independent and generic, enabling end-to-end tracking of products through various stages of the supply chain. It offers transparency, reliability, and public accessibility by using smart contracts to manage interactions and data integrity. The application supports tracking multiple object combinations and transformations in a flexible, use case-agnostic manner, enhancing traceability for producers and end users.
The SCT system uses the Ethereum blockchain and smart contracts to ensure data integrity, transparency, and immutability. It is designed as a decentralized application (Dapp), making it platform-independent and flexible. The system tracks products through QR codes, linking them to their supply chain history and supporting complex transformations and combinations of products. All transactions and data can be monitored and verified via block explorers, ensuring public accessibility and trust. This end-to-end tracking system adapts to various
supply chain scenarios, providing a versatile and reliable solution for managing product information [12].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Blockchain Scalability: Handling large transaction volumes in dynamic supply chains.
IoT Integration: Challenges in deploying and managing IoT devices across diverse supply chain environments.
Complexity of Tracking: Difficulty in accurately tracing and documenting transformations of complex objects.
Data Privacy: Concerns about privacy and security of sensitive supply chain information on the blockchain.
Interoperability: Integration challenges with existing supply chain systems and standards across industries or regions.
3.6 Food Traceability on Blockchain: Walmart’s Pork and Mango Pilots with IBM: Walmart, in collaboration with IBM, implemented a blockchain-based food traceability system to enhance safety and transparency in its supply chain. Enabling end-to-end traceability from farm to table. Walmart successfully conducted pilots for tracking pork in China and mangoes in the Americas, significantly reducing tracking time and promoting transparency. The initiative addresses challenges in food safety and waste reduction, aiming to revolutionize the global food ecosystem by fostering collaboration among key stakeholders.
Walmart's food traceability initiative, developed in partnership with IBM, utilizes blockchain technology based on Hyperledger Fabric to ensure data integrity and transparency throughout the supply chain. Mandatory and optional attribute lists are adhered to, ensuring consistency and interoperability among ledger participants. Smart contracts automate interactions, while key data attributes are recorded for each item, facilitating end-to-end traceability. Collaboration with industry leaders establishes common standards and guidelines, enhancing supply chain transparency and trust [13].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Scalability: Handling large data volumes efficiently.
Interoperability: Integrating with diverse systems seamlessly.
Complexity: Tracking intricate supply chain transformations.
Security: Ensuring data privacy and protection.
Adoption: Overcoming resistance and promoting widespread use.
3.7 AgriBlockIoT: is a decentralized, blockchain-based traceability solution designed for Agri-Food supply chain management. It seamlessly integrates IoT devices to produce and consume digital data along the supply chain. By leveraging blockchain technology, AgriBlockIoT ensures transparency, fault-tolerance, immutability, and auditability of records, addressing issues such as data integrity and single points of failure commonly found in centralized systems.
AgriBlockIoT integrates blockchain and IoT technologies to create transparent and auditable records for Agri-Food supply chain management. It utilizes two blockchain implementations, Ethereum and Hyperledger Sawtooth, to achieve traceability, adhering to industry-standard protocols and smart contract languages. The solution defines a use-case from farm to fork, deploying and evaluating performance metrics for both implementations. It considers trade-offs between scalability, reliability, and economic costs, while also customizing records and business logic to handle complex objects and transformations within the supply chain. Additionally, plans include extending performance analysis to assess real-world applicability with IoT devices and gateways [14].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Scalability: Difficulty in handling large transaction volumes efficiently.
Interoperability: Challenges in integrating with diverse systems seamlessly.
Complexity: Managing intricate supply chain transformations effectively.
Resource Intensiveness: High computational demands, especially for IoT devices.
Maturity: Limited readiness of Hyperledger Sawtooth compared to Ethereum.
3.8 Blockchain-based Agri-Food Supply Chain: A Complete Solution: is a comprehensive blockchain-based system for Agriculture and Food (Agri-Food) supply chain management. It addresses the challenges of traceability, trust, and accountability within the supply chain network. The solution ensures the immutability of data while enhancing traceability and reliability..
The solution utilizes blockchain and smart contracts deployed on the Ethereum network to establish a comprehensive system for Agriculture and Food (Agri-Food) supply chain management. Data is stored securely on the Interplanetary File Storage System (IPFS), ensuring efficiency and reliability. Smart contracts with algorithms facilitate interactions between supply chain entities, while adherence to blockchain standards and protocols, particularly those related to Ethereum, ensures robustness. The approach includes end-to-end traceability, trading, delivery, and reputation management within the Agri-Food supply chain, with plans to integrate refund mechanisms and implement a reputation system to address fake reviews and security threats [15].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Trust establishment challenges.
Complex supply chain decentralization hurdles.
Review authenticity concerns.
Implementation and security challenges.
Resource-intensive smart contract execution.
3.9 Blockchain-based Soybean Traceability in Agricultural Supply Chain: Establish traceability in the agricultural supply chain, focusing on soybean tracking. By eliminating the need for centralized authorities and intermediaries, the solution aims to enhance efficiency, safety, and transparency.
The solution utilizes Ethereum blockchain and smart contracts to establish traceability in the agricultural supply chain, specifically for soybean tracking. The approach includes a generic framework applicable to various crops and produce, with future plans to address scalability, governance, privacy, and standards, while integrating automated payments and proof of delivery using cryptocurrency. Transactions are recorded on the blockchain's immutable ledger, linked to a decentralized file system (IPFS), ensuring integrity and reliability throughout the supply chain ecosystem [16].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Scalability: Difficulty in handling large transaction volumes and data in dynamic supply chains.
Governance: Complexities in establishing governance mechanisms for decentralized networks.
Identity: Challenges in ensuring the authenticity and integrity of identities on the blockchain.
Privacy: Balancing transparency with privacy concerns in interconnected supply chains.
Compliance: Meeting industry standards and regulatory requirements across regions.
3.10 DL-Tags: utilizes Distributed Ledger Technology (DLT), specifically the Ethereum blockchain, to manage Smart Tags in supply chain management. These Smart Tags, incorporating technologies like RFID, NFC, and QR-codes, are deployed on products to provide traceability throughout their lifecycle. DL-Tags aims to decentralize and ensure the privacy and authenticity of data associated with these Smart Tags, allowing stakeholders and consumers to verify product information without revealing their identity. It offers a cost-effective and verifiable approach to supply chain management, presenting a practical solution for brand protection and anti-counterfeiting.
DL-Tags approaches supply chain mapping with complex objects by leveraging Smart Tags and the Ethereum blockchain. Each Smart Tag contains detailed information about the product's origin, journey, and current state, allowing for comprehensive tracking throughout the supply chain. As complex objects undergo transformations, such as processing or assembly, these changes are recorded on the blockchain through smart contracts. This ensures that all stakeholders have access to real-time, immutable data about the product's history and status, enabling accurate supply chain mapping even as objects undergo various transformations [17].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Scalability: Handling large transaction volumes in complex supply chains may strain the solution's capacity.
Cost: The expenses associated with deploying and executing transactions on Ethereum could be prohibitive.
Complexity: Integrating DL-Tags across diverse stakeholders and systems may require significant resources.
Blockchain Dependence: Relying solely on Ethereum may limit adaptability to evolving regulations.
Privacy Concerns: Maintaining privacy while using a decentralized approach could be challenging.
3.11 Smart Contract-Based Product Traceability System in the Supply Chain Scenario: is a product traceability system leveraging blockchain technology, where all product transfer histories are recorded in an immutable ledger using smart contracts. This system aims to address issues of transparency, data tampering, and accountability in traditional centralized traceability systems. It employs decentralized characteristics to reduce the risk of data tampering and includes an event response mechanism to verify transaction validity. Additionally, it allows consumers to participate in the network, enhancing information flow across the entire supply chain.
Regarding the approach to supply chain mapping with complex objects undergoing transformations, the system employs blockchain technology and smart contracts to track product transfer histories. Each transaction is recorded in an immutable ledger, the event response mechanism verifies transaction authenticity, ensuring the integrity of the supply chain data [18].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Scalability: Handling high transaction volumes in dynamic supply chains with complex objects can strain blockchain systems.
Interoperability: Integrating blockchain with existing systems in interconnected supply chains poses challenges.
Data Privacy: Ensuring privacy of sensitive information remains a concern in blockchain-based solutions.
Complexity: Implementing and managing blockchain solutions requires technical expertise.
Cost: Maintaining blockchain infrastructure can be expensive, especially for smaller stakeholders.
3.12 Food Safety Traceability System based on Blockchain and EPCIS: is a blockchain-based food safety traceability system that integrates EPCIS technology. It addresses issues like data invisibility and tampering prevalent in traditional systems by leveraging blockchain's decentralized and immutable nature. Through the use of smart contracts and collaborative management of on-chain and off-chain data, the system ensures data integrity while reducing the data explosion problem associated with IoT devices. Built on Ethereum, the prototype demonstrates efficient query response times and transaction throughput.
Through the use of smart contracts, it manages data interactions among participants, preventing tampering and ensuring data integrity. Collaborative management of on-chain and off-chain data addresses the data explosion issue associated with IoT devices, facilitating efficient tracking of complex objects undergoing transformations. By incorporating enterprise-level smart contracts, the system verifies the identity of participating enterprises while maintaining information security. This decentralized approach offers a tamper-proof and privacy-protected solution for food safety traceability, overcoming limitations of traditional systems [19].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Scalability: Difficulty in handling large volumes of data.
Data Privacy: Challenges in maintaining confidentiality.
Interoperability: Issues with integrating with existing systems.
Adoption Complexity: Technical expertise and resource requirements.
Regulatory Compliance: Keeping up with evolving regulations.
3.13 Grain Quality Assurance Tracking based on a Blockchain Business Network: proposes using blockchain technology. By implementing a blockchain-based business network, it aims to enhance efficiency and resilience in quality measurement processes during grain transportation. Addressing challenges such as delays and fraud. Additionally, it offers transparency and governance improvements by allowing all network participants to share the same business rules and transaction data.
The solution utilizes blockchain technology and smart contracts to track grain quality assurance in the agricultural supply chain. Through distributed ledger technology and smart contracts, transactions related to grain quality can be securely recorded and monitored throughout the supply chain. By establishing a blockchain-based business network, participants share transaction data and common rules, enhancing transparency and governance. Standards like cryptography ensure transaction security. Collaborative efforts define consensus principles for settlements, enabling effective supply chain mapping and seamless tracking of complex objects through transformations [20].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Data privacy concerns in decentralized setups.
Complexity in managing smart contracts securely.
Difficulty in achieving consensus among stakeholders.
High setup and maintenance costs.
Regulatory compliance uncertainties.
Limited technology adoption among stakeholders.
3.14 Tracing manufacturing processes using blockchain-based token compositions: The solution offers a blockchain-based approach to supply chain management, focusing on tracing manufactured goods and their components. Utilizing non-fungible digital tokens, each batch of products and their inputs is recorded transparently on the blockchain.
The solution utilizes blockchain and non-fungible digital tokens to enable transparent traceability of complex objects undergoing transformations in the supply chain. Smart contracts enforce "token recipes" that define product components, ensuring a clear link between goods and their inputs. As products are produced, input token consumption is logged, ensuring complete traceability from origin to retail.This addresses limitations of existing systems by providing comprehensive provenance information and documenting transformations throughout production. Enforced through smart contracts, the approach enhances transparency and accountability across the supply chain, starting from resource exploitation [21].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Complexity: Implementing token compositions and smart contracts for each batch of products can be complex and resource-intensive.
Scalability: As the number of products and components increases, scalability issues may arise, affecting the performance of the system.
Data Integrity: Ensuring the accuracy of data input and token compositions while maintaining data immutability remains a challenge.
3.15 TokenTrail Blockchain-based application for the traceability of complex assembly structures: addresses the traceability challenges in complex assembly structures. Utilizing a consortium Ethereum network and the ERC 1155 token standard, TokenTrail ensures trust and transparency across manufacturing flows. Its assembly token manager allows direct representation of unique parts and batches within smart contracts, simplifying traceability from raw materials to final products.
TokenTrail employs a consortium Ethereum network and the ERC 1155 token standard for traceability. Its Proof of Authority consensus ensures network reliability. The assembly token manager facilitates direct representation of parts and batches in smart contracts, enhancing supply chain mapping. A user-friendly interface simplifies data access, aiding stakeholders' decision-making [22].
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Scalability: Blockchain may struggle to handle the volume of transactions in dynamic supply chains.
Integration Complexity: Incorporating blockchain into existing systems can be technically complex.
Standardization: Lack of standardized protocols and interoperability may pose challenges.
Data Privacy: Balancing data privacy with transparency is a complex task.
Cost: Implementing blockchain solutions can be expensive, particularly for smaller enterprises.
3.16 Palmyra Platform (Cardano Solution): The Palmyra Platform is zenGate’s flagship product, a paradigm-shifting ecosystem which enables the tokenization and listing of certified commodities to be traded between businesses around the world.
Palmyra connects the full ecosystem of stakeholders across the value chain, providing a cheaper, more transparent and accessible enterprise-grade solution to users. Currently live and operational in emerging markets across APAC and Africa. Palmyra utilizes The Winter Protocol that is a simple open-source turn-key solution for traceability and tokenization technology developed by zenGate Global. It is specifically tailored for eUTXO blockchains, agnostic to the standard used for recording traceability data [23].
The protocol contains the following trace events :
Object
Aggregation
Transformation
Association
Transaction
Error Declaration
Zengate develops a Traceability Metadata Standard:
V1 standard of traceability data stored offchain via decentralized storage such as IPFS
Architecture
The backend follows a modular and scalable architecture, leveraging the capabilities of Nest.js. It is designed to work seamlessly with the winter-cardano library, which handles the core functionality of the Winter protocol.
The main components of the backend include:
Blockchain Endpoints: These endpoints handle interactions with the Cardano blockchain, such as tokenizing commodities, recreating commodities, spending commodities, and retrieving commodity details. They utilize the winter-cardano library to build and submit transactions.
Database Integration: The backend integrates with a PostgreSQL database using TypeORM to store and retrieve data related to transactions and commodities. It also uses Redis for managing UTXO (Unspent Transaction Output) to prevent double-spending errors.
REST API: The backend exposes a REST API that allows clients to interact with the Winter protocol. The API endpoints are organized into two main categories: blockchain endpoints and database endpoints.
Scalability and Modularity
Nest.js was chosen as the framework for the Winter Cardano backend due to its modularity and scalability features. It provides a structured and extensible architecture that allows for easy maintenance and growth of the application.
The modular design of Nest.js enables the separation of concerns and promotes code reusability. Each module encapsulates a specific functionality, making it easier to develop, test, and maintain individual components of the backend.
Performance and Efficiency
The Winter Cardano backend is designed to handle a high volume of requests efficiently. It leverages the power of Node.js and its event-driven, non-blocking I/O model to handle concurrent requests and maximize throughput.
The backend also implements efficient UTXO management using Redis to ensure the integrity of transactions and prevent double-spending. It intelligently selects available UTXOs and handles scenarios where UTXOs are being spent in the mempool.
Limitations when being applied in dynamic, interconnected supply chains involving complex objects:
Blockchain Scalability: Managing high transaction volumes in dynamic supply chains may strain the system's scalability.
Integration Complexity: Integrating the Palmyra Platform into existing systems might be technically intricate.
Data Standardization: Maintaining consistent data formats and standards across stakeholders could be challenging.
Adoption Hurdles: Achieving widespread adoption could face resistance due to various factors.
4. Limitations of Existing Blockchain-Based Traceability Architectures
For 1-13 blockchain-based traceability solutions only handle basic tracking of individual items and struggle to adapt to more complex supply chain scenarios involving changes in composition or structure.
When looking deeper into the traceability solutions found in the research, especially in relation to mapping complex supply chains with objects undergoing compositional changes, three main advanced architectures are mentioned: those by Westerkamp [21], Kuhn [22] and The winter protocol [23].
Put simply, these advanced traceability architectures use object tokenization and establish token ecosystems that enable users to carry out supply chain events related to objects in any order they choose. Moreover, these solutions outline methods to combine tokens with unique token IDs and "merge" them into a fresh token, facilitating on-chain tracking of compositional changes, such as component assembly.
Essentially, blockchain tokens serve as digital representations that can be owned and represent assets, currency, or access rights within a blockchain context. Because these tokens can embody different states and interact with one another, blockchain architectures built around tokens enable the linking of object-related supply chain event data, thereby offering traceable production information throughout the supply chain.
Considering the object-related supply chain events outlined by EPCIS and the functionalities of the utilized token standards, an examination of advanced traceability architectures highlights several constraints when implemented in dynamic, interconnected supply chains dealing with complex objects that undergo compositional changes.
To summarize, the limitations of the identified traceability solution in dynamic, interconnected supply chains involving complex objects with compositional changes are as follows:
1. Governance Concept: While Kuhn et al. [22] propose a governance concept integrated into their architecture, it is specific to the selected blockchain platform. This limitation prevents the transfer of governance logic to other blockchain platforms that are not exclusive to the architecture, necessitating administration of involved parties at an application level.
2. Token Deletion: Advanced architectures lack explicit mechanisms for token deletion. While some architectures, like this by Westerkamp et al. [21], incorporate token "consumption" or "burning," this functionality does not directly delete tokens. Instead, it marks consumed tokens to prevent their reuse, potentially leading to the creation of redundant "waste tokens."
3. Token Aggregation: The ERC-721 non-fungible token (NFT) standard, utilized in some architectures, faces limitations in mapping objects with varied assembly complexity. Although Kuhn et al. [22] adopt the ERC-1155 token standard to address this issue, it only allows for minting fungible token batches of the same type, posing challenges when mapping multiple non-fungible assemblies with non-fungible inputs of the same type.
4. Token Disaggregation: Architectures primarily focus on token "splitting," which distributes shares of token batches to different owners. However, neither approach effectively restores previously aggregated tokens, representing a limitation in achieving true token disaggregation according to EPCIS standards.
Important note: The winter protocol is the only architecture that successfully covers token aggregation and disaggregation.
5. Conclusion
In recent blockchain projects, the focus has been primarily on enhancing transparency within food supply chain management. Currently, there are no solutions available that specifically target the transparency enhancement and mapping of assembly processes in supply chains dealing with complex components. These supply chains involve various elements such as raw materials, intermediate components, final products, and transformation events, each with distinct properties. However, they often interact or merge with one another within complex manufacturing processes. Surprisingly with the exception of the Palmyra platform using the winter protocol, none of the examined scientific publications address the comprehensive coverage of complex supply chains, spanning from raw materials to final products, while also considering transformation events.
A comprehensive token-based architecture could mark a significant advancement in making blockchain technology's features accessible to intricate manufacturing networks.However, factors like blockchain scalability may also constrain its applications in intricate manufacturing networks. These aspects are not within the scope of this research and require further exploration. Presently, I´m engaged in ongoing research to develop a comprehensive Cardano tokens-based architecture.
6.References
Olsen, P.; Borit, M. How to define traceability. Trends Food Sci. Technol. 2013, 29, 142–150. [Reference]
GS1 Global Traceability Standard, version 2.0; GS1’s Framework for the Design of Interoperable Traceability Systems for Supply Chains. GS1: Brussels, Belgium, 2017
Konovalenko, I.; Ludwig, A. Event processing in supply chain management—The status quo and research outlook. Comput. Ind. 2019, 105, 229–249. [Reference]
EPCIS. EPC Information Services (EPCIS) Standard. 2016. Available online: https://www.gs1.org/sites/default/files/docs/epc/EPCIS-Standard-1.2-r-2016-09-29.pdf(accessed on 5 September 2022).
Gross, T.; MacCarthy, B.L.; Wildgoose, N. Introduction to dynamics of manufacturing supply networks. Chaos Interdiscip. J. Nonlinear Sci. 2018, 28, 093111. [Reference]
Specification—Details of the Asset Administration Shell: Part 1—The Exchange of Information between Partners in the Value Chain of Industrie 4.0; Plattform Industrie 4.0. Federal Ministry for Economic Affairs and Climate Action (BMWK): Berlin, Germany, 2022.
Abeyratne, S.A.; Monfared, R.P. Blockchain ready manufacturing supply chain using distributed ledger. Int. J. Res. Eng. Technol. 2016, 5, 1–10. [Reference]
Malik, S., Kanhere, S.S., Jurdak, R.: ProductChain: Scalable Blockchain Framework to Support Provenance in Supply Chains. International Symposium on Network Computing and Applications (NCA) 17, 1–10 (2018). doi: 10.1109/NCA.2018.8548322 [Reference]
Arena, A., Bianchini, A., Perazzo, P., Vallati, C., Dini, G.: BRUSCHETTA: An IoT Blockchain-Based Framework for Certifying Extra Virgin Olive Oil Supply Chain. IEEE International Conference on Smart Computing (SMARTCOMP) 7, 173–179 (2019). doi: 10.1109/SMARTCOMP.2019.00049 [Reference]
Zhang, X., Sun, P., Xu, J., Wang, X., Yu, J., Zhao, Z., Dong, Y.: Blockchain-Based Safety Management System for the Grain Supply Chain. IEEE Access 8, 36398–36410 (2020). doi: 10.1109/ACCESS.2020.2975415 [Reference]
Tsang, Y.P., Choy, K.L., Wu, C.H., Ho, G.T.S., Lam, H.Y.: Blockchain-Driven IoT for Food Traceability With an Integrated Consensus Mechanism. IEEE Access 7, 129000–129017 (2019). doi: 10.1109/ACCESS.2019.2940227 [Reference]
Niya, S.R., Dordevic, D., Nabi, A.G., Mann, T., Stiller, B.: A Platform-independent, Generic-purpose, and Blockchain-based Supply Chain Tracking. IEEE International Conference on Blockchain and Cryptocurrency (ICBC) 2019, 11–12. doi: 10.1109/BLOC.2019.8751415 [Reference]
Kamath, R.: Food Traceability on Blockchain: Walmart’s Pork and Mango Pilots with IBM. The JBBA 1(1), 1–12 (2018). doi: 10.31585/jbba-1-1-(10)2018 [Reference]
Caro, M.P., Ali, M.S., Vecchio, M., Giaffreda, R.: Blockchain-based traceability in Agri-Food supply chain management: A practical implementation. IoT Vertical and Topical Summit on Agriculture - Tuscany (IOT Tuscany), 1–4 (2018). doi: 10.1109/IOT-TUSCANY.2018.8373021 [Reference]
Shahid, A., Almogren, A., Javaid, N., Al-Zahrani, F.A., Zuair, M., Alam, M.: Blockchain-Based Agri-Food Supply Chain: A Complete Solution. IEEE Access 8, 69230–69243 (2020). doi: 10.1109/ACCESS.2020.2986257 [Reference]
Salah, K., Nizamuddin, N., Jayaraman, R., Omar, M.: Blockchain-Based Soybean Traceability in Agricultural Supply Chain. IEEE Access 7, 73295–73305 (2019). doi: 10.1109/ACCESS.2019.2918000 [Reference]
Bencic, F.M., Skocir, P., Zarko, I.P.: DL-Tags: DLT and Smart Tags for Decentralized, Privacy-Preserving, and Verifiable Supply Chain Management. IEEE Access 7, 46198–46209 (2019). doi: 10.1109/ACCESS.2019.2909170 [Reference]
Wang, S., Li, D., Zhang, Y., Chen, J.: Smart Contract-Based Product Traceability System in the Supply Chain Scenario. IEEE Access 7, 115122–115133 (2019). doi: 10.1109/ACCESS.2019.2935873 [Reference]
Lin, Q., Wang, H., Pei, X., Wang, J.: Food Safety Traceability System Based on Blockchain and EPCIS. IEEE Access 7, 20698–20707 (2019). doi: 10.1109/ACCESS.2019.2897792 [Reference]
Lucena, P., Binotto, A., Da Silva Momo, F., Kim, H.: A Case Study for Grain Quality Assurance Tracking based on a Blockchain Business Network. Symposium on Foundations and Applications of Blockchain (2018) [Reference]
Westerkamp, M.; Victor, F.; Küpper, A. Tracing manufacturing processes using blockchain-based token compositions. Digit. Commun. Networks 2020, 6, 167–176. [Reference]
Kuhn, M.; Funk, F.; Zhang, G.; Franke, J. Blockchain-based application for the traceability of complex assembly structures. J. Manuf. Syst. 2021, 59, 617–630. [Reference]
The Winter Protocol [Reference]