Main drivers of value creation with DLT in the manufacture industry

Abstract
When talking about the 4th industrial revolution, its impact on markets growth and the different elements that constitute it, distributed ledger technology (DLT) is often mentioned after searching in detail about how to reach such desired scenarios. The range of its application goes from the financial sector to health and pharmaceutics, but those were just initial trending topics used to exemplify the benefits of this technology. Blockchain as is also known is currently engaging in all stages of the supply chain management and product life cycle in traditional market segments as well. This situation can directly and indirectly be related to the value creation process that occur inside manufacture firms and to the conditions that improve the way companies in this industry serve customers according to their needs (Isaja & Soldatos, 2018). In the following paper, a brief introduction and description of Blockchain technology is going to be presented. The different approaches on ways to implement DLT in the manufacture industry while creating value would be confronted with familiar and well-studied issues that manufacture companies face on all levels of the strategic decision-making process.
Keywords: DLT, Manufacture, Blockchain, IoT, Cloud Manufacture Based.
Main drivers of value creation with DLT in the manufacture industry
With the purpose of settling a common ground to match value creation functions on the manufacture industry with current applications of DLT, some technical concepts and explanation regarding both Blockchain technology and production management theory is presented in the initial part. In the next step, different examples on where the value is created (or destroyed) during the product life cycle are faced with the advantages that DLT technologies provide as an essential element to deal with uncertainty coming from current complex supply chain networks and other sources of troubles that organizational functions usually deal with.
Definitions
The concept of a distributed organized network with unmodifiable data and time stamp is quite old. In 1991, Stuart Haber and W.Scott Storneta presented a paper on this topic but was at the time, for the most part ignored. Certain events occur since then, but only until 2008 Satoshi Nakamoto capture back public attention with the introduction of a new digital currency: The Bitcoin (Yun, Ferreira, & BlockstreetHQ, 2018). Oddly enough, this situation came first with an undesired effect. Among the different literature reached for the elaboration of this paper, a common denominator regarding initial implementations of block chain technology on the industrial context was the fact of wrongly relating DLT with cryptocurrency environments, making it hard to pitch. Fortunately, this misconception has been changing as transparency and traceability requirements increase with the implementation of new procedures and methods involving Internet of Things (IoT) and Cloud based Manufacture models CBM; requirements that DLT can fulfill.
In a nutshell, Blockchain refers to a distributed set of data or blocks that constantly records transactions after common consensus on its veracity (Bahga & Madisetti, 2016). The maintenance of the network as well as the verification tasks are conducted by nodes which are encouraged to do so by means of monetary or other types of incentives. This linear allocation (ledger) of blocks is stored among the different agents that interact with it, making it decentralize by nature. On the other hand, several protocols like Proof of Work or Proof of Stake allow the model to self-monitor and create trust regarding what information is being added at any point in time. Each block, in addition to transaction information contains a time stamp and a digital fingerprint which refers to the previous block also known as hash, making it extremely hard to modify once is already on the chain. Depending on the type of Blockchain, whether it is private-public, permissioned-permissionless, roles and keys both public and private are essential to determine the interaction among all participants (Li, Barenji, & Huang, 2018).
To understand when Blockchain technology is suitable for a particular application, the following items must be presented:
• Lack of trust among agents (human-human, human-machine, machine-machine).
• High incentive on external influences to hack, modify, or explode system’s vulnerabilities.
• A current third party(s) which develop the required activities that the 2 previous statements involve.
In this context, the IoT provide an opportunity never seen before in terms of production and efficiency growth, comparable perhaps to the revolution achieved after the introduction of computing or the industrial revolution itself. The magnitude of the upcoming events, where machines are connected to each other, executing contracts with no human interaction is quantified in around 1 trillion USD for the upcoming years (Abeyratne, 2016). The economy as a pie, will for sure once again get bigger and bigger as repetitive tasks with no value to the product or service become obsolete and uncertainty in logistics and operation research is drastically reduced.
Smart contract refers to a set of unique addressed functions that are executed after a transaction which changed a desired state took place. They are triggered by conditions but self-executed without requiring any intermediary (like a bending machine) (Blu, 2018). Smart contracts can help companies and customers to track relevant information of certain parts or components and make it transparent. This ensures in time deliveries and fair payments of suppliers along the supply chain end-to-end.
Etherium is among the most common open Blockchain platform. The Ethidium Virtual Machine (EVM) enable the execution of small contracts in a sandbox environment, reducing the risk of threats from untruthful codes. Harmless and verified codes can then be ran, so there is redundancy to compensate the lack of trust. Different externally owned accounts (EOA) can then interact with others EOA or with contract owner accounts (COA) which are controlled by codes after transactions took place (Boschi, Borin, Raimundo, & Batocchio, 2018).
From the operation research point of view, traditional strategies in competitive environment like capacity excess in duopolies involve the use of capacity to gain an advantage in simultaneous non-cooperative games. In this regards, it is hard to come about the actual information on investments without requiring the intervention of third parties (Lowson, 2010).
DLT will allow optimal capacity sizing by reducing the lack of information on demand, increasing the usage of space and reducing the costs of under and overages stocks.
From decision tree analysis to technology portfolio investments and replacements, more accurate and faster information will impact all functions (support and value creation) inside the organization, benefiting both the manufacture industry and the consumer. 
DLT drivers of value creation on the manufacture industry
Today applications of IoT involve cloud based structures which manage the interactions among participant in a centralize manner. Dependency on a finite number of servers represent an attractive target for hackers and other parties. In this regards, DLT can enhance CBM so no trusty intermediary is required with the implementation of smart contracts, enabling accessing to resources according to demand with little managerial effort. Solutions as BPIIoT already provide decentralized peer-to-peer network interaction for industrial applications based on Blockchain (Bai, Hu, Liu, & Wang, 2019).
From the value creation point of view, safer interactions machine-machine in manufacturing processes allow integration of job-shop stations in clouds environments, on demand access to manufacturing resources and tasks automation such as maintenances and inventory records. Imagine a factory where machines order them-self the parts needed to be changed for an upcoming maintenance phase with no human interaction. No place for delays or ordering errors is left. Defects sources can be quickly identified as well as infrastructure usage and utility of manufacture means. The costs and effort saved on dealing with those tasks can then be translated into design and quality activities which transform at the end in a competitive advantage for the firm.
Undesired effects such as the bullwhip, where individual forecast result in inefficiency and slow reaction times can be controlled by having direct and transparent communication: from the raw material supply to the final product. Increasing in size inventory can be substituted by just-in-time techniques, reducing inventory costs and serving the customer exactly what they wanted and when they needed it (Tan & Matthews, 2013).
On the other hand, some argue that this increasing exchange of information can affect business competition and strategies, since everyone would be seeing everything at all time. As any new disruptive technology, market supply and demand combined with proper regulation will balance this flow of information.
DLT technology will at the same time enhance Industrial Cyber-Physical Systems (ICPS), where factories check production feasibility with help of a digital twin, controlling and adjusting manufacturing processes. Mass customization with matching consensus among peers will be achieved thanks to smart contracts (Hughes, Park, Kietzmann, & Archer-Brown, 2019).
Consumer habits have evolved as well, and with that the attributes that represent value on a particular product for them. Ethical aspects regarding source of raw material can shift customer attention toward a particular product. On one hand, the customer seeks to satisfy a need while knowing that in such process no harm on other humans or the environment has been created. On the other hand, companies can use DLT to track all individual parts from second and third tier, optimally selecting their suppliers while validating their quality certifications. Transparency enables awareness which results in better decision making strategies. Durability, transparency, immutability and process integrity will reduce operational tasks efforts, transform the manufacture industry from inefficient the current use of resources, reduce dependency on uncertain events or broken communication channels and benefit the customer and the environment while bringing value to the final product and service.
 
References
Abeyratne, S. A. (2016). Blockchain Ready Manufacturing Supply Chain Using Distributed Ledger. International Journal of Research in Engineering and Technology, 05(09), 1–10. https://doi.org/10.15623/ijret.2016.0509001
Bahga, A., & Madisetti, V. K. (2016). Blockchain Platform for Industrial Internet of Things. Journal of Software Engineering and Applications, 09(10), 533–546. https://doi.org/10.4236/jsea.2016.910036
Bai, L., Hu, M., Liu, M., & Wang, J. (2019). BPIIoT: A Light-Weighted Blockchain-Based Platform for Industrial IoT. IEEE Access, 7, 58381–58393. https://doi.org/10.1109/ACCESS.2019.2914223
Blu. (2018). Blockchain Manufacturing Is No Longer a Concept | Blockchain Central - YouTube. Retrieved January 31, 2020, from Blockchain Central website: