The definitions and explanation of all technologies that are incorporated in the supply chain digitization survey are mentioned below. These definitions are specifically defined for this survey.
Big Data is so huge and complex that it cannot be analyzed by using traditional database systems. Big Data is characterized by the 3V’s:
The Internet of Things (IoT) is the network of devices that are connected together and communicate with each other to perform certain tasks, without requiring human-to-human or human-to-computer interaction. The Internet of Things is about installing sensors (e.g. RFID, IR, GPS, laser scanners, etc.) for everything, and connecting them to the Internet through specific protocols for information exchange and communications. Example: based on the data received, a manufacturer will integrate design, and will optimize, manage, and monitor the production process in order to produce products efficiently. With the help of self-optimization and autonomous decision-making mechanism, machines and equipment will adopt more to improve the performance.
Derive information from significant amounts of (historical) data and answer the question of what happened.
Diagnostic analytics answers the question why it happened and determines what the biggest impact had.
Predictive analytics in supply chains derives demand forecasts from past data and answers the question of what will happen (e.g. time series methods, linear, non-linear and logistic regression, cluster analysis).
Prescriptive analytics derives decision recommendations based on descriptive and predictive analytics models and mathematical optimization models. It answers the question of what should be happening (e.g. Mixed-Integer Linear Programming, network flow algorithms).
Artificial intelligence is about giving machines the capability of mimicking human behavior, particularly cognitive functions. Examples would be facial recognition, automated driving, planning optimization.
Machine learning can either be considered a sub-field or one of the tools of artificial intelligence, is providing machines with the capability of learning from experience. Machine learning algorithms, also called “learners”, take both the known input and output (training data) to figure out a model for the program which converts input to output. The model can take the form of a set of “if–-then” rules.
Digital twin is a digital representation of a physical entity or system. Simulations leverage real-time data to mirror the physical world in a virtual model, which can include machines, products, and humans. Digital twin allows the analysis of data and monitoring of systems to forecast problems even before they occur. Example: The digital twin allows operators to test and optimize the machine settings for the next product in line in the virtual world before the physical changeover, thereby driving down machine setup times and increasing quality.
A blockchain is a distributed ledger that records and shares all transactions that occur within the blockchain network. The blockchain network consists of multiple nodes that maintain a set of shared state and perform transactions modifying the states. Blockchain will lead to openness, transparency, neutrality, reliability, and security for all supply chain partners. One of the best-known examples of blockchain is the cryptocurrency Bitcoin.
Cloud computing is the on-demand availability of computer system resources, especially data storage and computing power, without direct active management by the user. Cloud solutions provide flexibility, efficiency and security that for instance can be used to process the huge amount of data and linked products from the IoT.
Mobile devices can be used in multiple processes in the supply chain. Implementing mobile devices such as smartphones and tablets in the supply chain can lead to multiple advantages, such as: increased amount of data collection, tracking information, scan documents or capture signatures (logistics)
Augmented reality is a technology which enables a real-world environment with a digital overlay (e.g. Pokémon Go). As example: augmented reality can be used to support human workers while performing an operational task (e.g. picking, difficult assembly process and GPS)
Virtual reality is the creation of a virtual environment presented to our senses in such a way that we experience it as if we were really there. Virtual Reality can be used in the supply chain for multiple goals such as training, product design and problem solving. By applying VR, the physical product or problem does not have to be shown because a digital version can be inspected.
The smart factory is an important element of Industry 4.0. A smart factory is completely equipped with sensors, actors and autonomous systems interacting with each other to improve efficiency and to fulfil more complex tasks. A smart factory also has the ability to predict and maintain the machines to manage the factory system.
Algorithms that mimic human actions to reduce repetitive, simple tasks. RPA is generally not considered a form of AI because it is not improving or learning but only repeating.
Industrial robots that perform non-ergonomic, repetitive tasks (e.g. heavy lifting, difficult placement of parts, “third-hand” for assembly) in collaboration with human workers.
Advanced robots are able to perform complex task and can work in less-structured environments. Advanced robots are intelligent which means that they can provide and receive feedback from other parts of the production system, e.g. through the Internet of Things.
3D printing uses computer-generated designs to create "build paths" that reproduce a digital model through consolidation of materials with an energy source. The core of additive manufacturing applications to SCM is the usage of 3D printers at different stages in the SC to increase manufacturing flexibility, achieve shorter lead times, increase product individualization (economies of one) and reduce inventory.
In cyber-physical system, physical and digital components of the supply chain interact with each other by connecting physical objects via sensors to the digital system. A CPS consist of two main components: advanced connectivity for real-time data and intelligent data management for analytics. By integrating a cyber-physical system with production, a traditional factory can be transformed to an Industry 4.0 factory.
Digital product memories collect data in all phases of product process (e.g. parts production, assembly, distribution) and use this for analysis and adjustment. The function of a digital product memory is somewhat similar as the function of a black box in airplanes and records all relevant ambient parameters digitally. For example, bottles of milk and fresh bananas transported in a refrigerated truck can “complain” to the air conditioning that their critical values have been exceeded. Thereafter, the air conditioning can automatically adjust itself.
These are unmanned aircraft that are presenting potential use in supply chain. Drones can be used in last mile delivery or in warehousing.
E-procurement refers to the use of integrated technology systems for procurement functions (e.g. sourcing, negotiation, ordering). A special type of e-procurement is E-auctions. Benefits of E-auctions are among others: cost reductions, ability of real-time bidding, reduction in cycle time, increased geographical outreach and transparency in the process.
Serious gaming can be applied for both training new employees and training existing employees in a changing work environment. Simulations enhanced with gaming features, enables the learner to cope with real problems and authentic situations that are very close to reality.
Intelligent packaging offers additional benefits beyond the traditional packaging task by adding sensors to the packaging. Benefits include: real-time information about freshness or quality, marketing functions and protective functions (e.g. alarm the doctor if a patient takes a pill incorrectly).
Supply Chain simulation enables a company to analyze and experiment with its existing process in a virtual setting. Because all dynamics and uncertainties can be taken into account, simulation tools can help companies make decisions.
Autonomous-driving vehicles impact the supply chain in multiple ways. In the future it might be possible to have autonomous trucks on the highway but also in- and between- warehouses (or factories) can autonomous-driving vehicles improve efficiency in supply chains.
An advanced supply chain tool which analyses huge amounts of data from all the supply chain. By using these tools (e.g. Llamasoft) supply chain managers have more visibility in the end-to-end supply chain.
A Warehouse Management System (WMS) is a software tool to support warehouse operations. The software supports warehouse management in e.g. daily planning, organizing, staffing, directing, while supporting workers in the performance of material movement and storage in the warehouse.
A Transport Management System is used for managing transport in the supply chain. The main processes are planning, transportation execution, transport follow-up and measurement.
Electronic Data Interchange (EDI) is the electronic interchange of business information using a standardized format. This allows companies to exchange data efficient. Often an EDI is linked to the ERP so that the information is directly seen in the enterprise system.
Wearables can be used in a supply chain to, for example, collect data (e.g. smartwatch), support workers (e.g. smart glasses) and improve safety (e.g. smartwatch).
