4.0 Industry Technologies & Supply Chain


0 Industry Technologies & Supply ChainVictor RomanBlockedUnblockFollowFollowingNov 27, 2018The New Industry’s ParadigmIn modern society, the demand is increasingly sophisticated and personalized.

In the industry this means that in order to satisfy people and companies’ needs, it is essential to carry out a more efficient and intelligent way of production, maximizing the profitability of all the processes involved, radically reducing costs and marginal manufacturing times.

In short, optimizing production.

Currently, supply chains aren’t anymore just systems for keeping track of products along the chain, but they have become a way to gain a competitive advantage and even build an own brand.

Integration of technologies in smart factoriesThus, the fourth industrial revolution is characterized by the creation of intelligent factories, that implement and integrate state of the art technologies such as cyberphysical systems (which combine tangible assets with digital twins), IIoT (Industrial Internet of Things), data analytics, additive manufacturing, 3D printing and artificial intelligence.

Applying these technologies make possible to achieve the necessary optimization and automation to reduce costs and manufacturing times.

This will allow us to produce thousands of different product configurations and to manufacture very small batches of goods at a very low cost.

Supply chains are one of the main areas in which the use of these technologies can cause a revolution in the optimization and automation of processes.

The main problems that supply chains face currently are lack of transparency along the chain and the difficulty in tracing the goods that go through it.

Supply chain’s actorsIt is notorious the case of Maersk, the international containerized goods transport company that has the largest market share in its sector (approximately 20%).

The cost of managing the shipping of a container is currently higher than the cost of the physical transport of the container itself, due to the authorizations and procedures that must be carried out in the countries involved and the pertinent authorities.

In short, because of the lack of transparency of information and the traceability of assets, which slows down the entire process and raises dramatically costs.

That is the reason why the application and integration of the Internet of Things, Blockchain and Big data technologies, referring to the 4th industrial revolution will mark a turning point in the production processes, and this is what we will explore throughout the article.

IoT architechtureIn particular, IoT technologies are of special interest in this revolution, to the point that a new specific term was coined to refer to the application of these technologies in the 4.

0 industry context: Industrial Internet of Things (or IIoT).

The devices that are part of these scalable and integrable ecosystems must be subject to an extremely effective management, since authentication and communications between the different cyberphysical systems are key in these technologies, failures in the collection, processing or storage of the generated data may have catastrophic consequences throughout the production chain and even impact on human losses.

That is why the decentralized, immutable and integrated management of data is crucial and it is in this context that Blockchain technologies can provide a differential value.

Thanks to the application of this technology, the activity and identity of each integrated device can be recorded in the production system, without risk of manipulation of the data and its consequences.

Different network architechturesIn addition, the Blockchain can be integrated through communication protocols between machines, allowing the creation of a new economy between the devices themselves in which they can reach agreements on supplies of raw materials, energy, parts, maintenance, and even logistics, via Smart Contracts whose payment will be executed automatically once the previously established conditions are met.

There are already examples of micropayments through the Blockchain or the Tangle with sensors that sell their data, and electric cars that trade electric power between themselves and recharging points.

IoTA’s first recharging pointThis integration involves the streamlining and automation of hundreds of processes that currently require a large number of intermediate steps that hinder and increase the current production processes.

This added with the dramatic decrease in the need for intervention by regulatory (and human) third parties, will greatly reduce the consequent expense involved.

In this way, the reduction in marginal costs necessary to meet the needs of personalized and unitary production can be achieved.

The key is the disintermediation of the production process, so that companies can receive requests for a decentralized portal, incorruptible and easily accessible by all parties involved.

Once these data stored in secure and transparent networks is available, the technologies referring to the Data Science context (such as Data Analytics, Machine Learning and Big Data) allow the treatment of data.

This enables us to extract significant information and to perform an accurate and efficient predictive analysis of demand, part prices and maintenance to ensure the proper functioning of supply chains and production systemsData Dasboard for visual managementSupply Chain Objectives and Current InefficienciesFrom the point of view of a supply chain system based on products and customers, which requires collaboration between different agents such as buyers, suppliers, distributors … there are a number of objectives in which it is essential to emphasize:1) Efficiency in the sharing and treatment of data:The management of assets like inventory or transport of resources requires efficiency through collaborative efforts.

Sharing information efficiently between these parties can make the difference between delivering the goods in the right place at the right time, minimizing the cost and meeting the customer’s demands, or just the opposite, chaos.

It is therefore extremely important how information is shared and processed throughout operations.

2) Optimized transport and Logistics:Each agent involved in transporting, ordering and shipping goods relies on the optimization of activities that avoid high costs and poor synchronization.

Automatic transactions are very useful in this context, but especial care must be taken and a person has to periodically check the proper functioning of the system.

3) Feedback for Quality Improvement:Knowing where problems or deficiencies of the system are located will allow agents to focus on trustworthy information that points out vulnerabilities or mistakes made along the way.

This is based on the principle of effective management “What cannot be measured cannot be improved”.

4) Build Long Term Stability:Building a relationship of trust in the supply chain ecosystem can create stability in operations and strengthen collaborative plans, coordination and distribution of common business initiatives, resulting in the raising of the harmonize exchange of goods and whit it, a better customer-manufacturer relationship.

IoT Features Relevant to Supply Chain:IoT, is understood as the network of devices, vehicles and home applications integrated with electronics, software, sensors and actuators that are interconnected with the objective of collecting, storing and sharing information, with the possibility of performing certain actions with respect to it.

The notorious decrease in the price of microprocessors, controllers and sensors has allowed the proliferation of IoT systems that allow the collection, transmission and storage of a huge amount of data.

Currently, the concept goes far beyond Machine to Machine (M2M) communication and describes an advanced connection network for devices, systems and services that complies with a wide variety of protocols, domains and applications.

IBM’s example of IoT and supply chainIoT, and more specifically its industrial version, IIoT, are called to revolutionize supply chains in regards to operational efficacy and business opportunities and revenue for manufacturers.

The will achieve this via:1) Assets traceability:In the past, tracking of numbers and barcodes was carried out to manage goods along the supply chain.

Currently, RFID methods and GPS sensors can monitor the status and location of products from the time they are produced until they reach the end customer.

Being able to gain control over the management and quality of deliveries in time and the prediction of demand that it enables it’s a certain game changer.

2) Relationships with Suppliers:According to IBM, up to 65% of the value of company’s products is derived from its suppliers.

The data obtained by tracking assets allows manufacturers to optimize production scheduling and patterns recogition in relationships with suppliers, revealing significant business opportunities.

Therefore, it is crucial to pay special attention to the whole process involved with them, because a higher quality of service and product, drives to a better relationship with the client.

3) Stock and Predicitions:IoT sensors can track inventories and stock supplies for future manufacturing in a single click and also store information in shared spaces in the cloud easily accessible by all interested parties.

All this allows to make even more efficient production schedules.

4) Connected transports:Supply chains do not stop growing, both vertically and transversally, and it is increasingly important to ensure that all containers and fleets are connected, so that there is an integral and effective transmission of information along the entire chain of supply.

Blockchain Features Relevant to Supply Chain:In short, the Blockchain is an information storage system, secure, anonymous, decentralized and thanks to the cryptography with which it operates, free of manipulations.

Blockchain can be understood as a series of text files that contain the information that we want to save, forming a chain of blocks and in which each block contains information from the previous block, and this one from the previous one, and so on.

Block’s content and relationship between blocksTherefore, the Blockchain is a network of computers in which all the devices that are part of the network keep a copy of the network.

This is different from traditional database servers, where there is only one copy of the information, it is centralized in a single server, and each user searches on this server for information.

In contrast, the Blockchain can be found in all devices that make up the network, it is a decentralized and distributed database and this is the characteristic that makes the recorded information much more secure and difficult to be manipulated or lost, with respect to traditional databases, and that is what gives Blockchain the key to its success.

Consensus and intelligent contracts allow the blockchain to automate transactions that take place in the supply chain processes.

So it’s the case of current Blockchain applications that take advantage of this features such as Hyperledger and IBM’s solutions based on its technology.

IBM’s & Hyperledger solutionData Science Features Relevant to Supply ChainPredictive analysis is positioned as the most powerful tool capable of revolutionizing supply chains.

So much so that it is a sector that is expected to have a market value more than 9 trillion dollars by 2020.

The science of data and the ability not only to extract relevant information from them, but to make accurate predictions allows the capture of real-time decisions that will significantly improve the strategies and performance actions in this sector.

Data science fieldsMachine Learning is one of Data Science subfields that has grown ashtonisingly in the latest years.

It can be defined as:“Machine Learning is the science of getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions.

”It is, hand to hand with Deep Learning, the science that allow us to build systems with Artificial Intelligence, which can take advantage of computers capabilities in making millions of calculations per second and help tremendously in the decison making process and the automation of repetitive tasks.

Currently, these are ubiquitous technologies (which are part of our ecosystem and our day to day) and we find it from everywhere: from image recognition (that are able to detect cancer more accurately than doctors), to game-engines (that can beat world’s greatest Go player), chatbots and fraud detectors.

The engine of these technologies is the astonishing amount of data that is available to us today.

Due to the large drop in the price of technology and sensors, we can now create, store and send more data than ever in history.

Up to ninety percent of the data in the world today has been created in the last two years alone.

There are 2.

5 quintillion bytes of data created each day at our current pace and this pace is only expected to grow.

This data feeds the machine learning models and it is the main driver of the boom that this science has experienced in recent years.

Concretely, data analysis and the application of machine learning models, will affect three main areas of supply chains:1) Demand Prediction:The effective prediction of future demand of products and goods based on past events and trends is a key component for the improvement in after-sales service without having to increase costs.

The application of these technologies allows to elimination of overstock and allows warehouses to work between them, increasing the integrity and fluidity of the supply chain, with the main objectives of achieving high levels of availability of service parts, operating time of the product with minimal risk and better customer service.

2) Predictive Pricing:The classic treatment of this area is through spreadsheets, based on the past prices to assess the prices of service parts.

The problem is that parts and products are sold at different prices in different locations, which translates into poor customer experience and lost opportunities to obtain benefits for manufacturers.

By using predictive algorithms to estimate the price of the parts, manufacturers must take into account the different factors that affect sales, including the location of the parts, seasonality, weather and demand.

Machine Learning models allow to take into account all these factors and therefore to make a far more precise adjustment of the prices.

3) Predictive Maintenance:The break-fix service is reactive and inefficient.

Up to 55% of services fail because the service part is not available when needed, which translates into an increase in product downtime, stock breakdowns, loss of revenue for the product owner and a customer dissatisfied.

With the synergistic integration of IoT and predictive analysis, the different parties will be able to detect and communicate when service parts are close to failure and therefore, the manufacturer can determine when new parts are needed, proactively directing them to a distributor or repair center instead of storing them, taking up stock space.

All this allows to reduce an excess of inventory and the additional cost associated with it.

In addition, improving of the ratios of filling of parts, avoiding the cost and corruption of unscheduled downtime and ultimately improving customers experience.

ConclusionThe integration of IoT technologies with Blockchain and Big Data can solve many of the problems faced by supply chains.

Applying industry 4.

0 technologies enable us to monitor each part of the processes of supply chains in real time with IoT, to verify the integrity and transparency of the data, to set up an economy between devices via smart contracts with Blockchain, and to make precise predictions regarding demand, price and maintenance of the service parts with Data Science.

All this translates into a radical improvement of the efficacy and efficiency of the production process and leads to the necessary optimization that is compulsory to face the new needs of the public, to give an optimal customer experience and ultimately to improve industry’s ecosystem.

This results in savings for manufacturers, which translates into a better service to customers and culminates in an improvement in the quality of life of people.

Which positions us on the path of sustainable growth.

My intention with this article was to help you to understand the current paradigm of technology and its applications to the industry, concretely in supply chain.

In order to encourage you to keep learning about these technologies and to explore their infinite possibilities.

Future is bright and with everyone’s collaboration we will be able to achieve our goals much faster.

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