Manufacturing industry is one of the pillars of the European economy. Not surprisingly, digitization in manufacturing is a core topic in research agendas and in industry. The manufacturing sector is a traditional sector with a broad variety of individual challenges. Regarding CPS platforms, even different disciplines within production have varying requirements. The triangle of “cost, quality and deployment” is a basic requirement of the producing industry. The scenarios address these requirements on different levels and specify the understanding of the CPS platform environment.
Value networks are complex systems with many dependencies, which are hard to grasp for single persons or companies in such a network. Decisions in this environment are based on heterogenous data sources from different partners in the network. In future value creation networks, the entities will share relevant information to optimize the overall system with respect to cost savings, increase of robustness and availability of resources. Operators of factories will be supported in decision making on operational questions regarding their suppliers and customers. Automated decisions, decision support and encapsulation of complexity are key to enabling digitization. However, security and privacy issues are solved to equally involve partners in the value network.
Customer and users: operations managers, plant managers, responsible persons in supply chain management, operative employees in production and operations management.
Societal/Human: The human will be in the loop for final decision making in different degrees. Decision makers will be highly included for strategic decisions (like investments for new facilities) and excluded for “standard” decisions on a regular base (like inventory refill by automated buying decisions). The human gets support regarding complex systems to make better decisions about sourcing of material or deployment strategies. Information systems support the aggregation of information for the worker (operator assistance systems).
Processes: Business processes are optimized based on near real-time and real-time information from supply chain processes and the status of network partners. Information about processes and equipment are transparent to the operator of a factory. Negotiations between partners about sourcing/deployment are partially or fully automated.
Information: Anonymous information is available to partners in the value network, while partners can be operators of plants or platforms. Systems will use data from processes to predict performance. Data based models for predications of demands and capacity will be shared amongst participants in the network. A large amount of data is processed to get to decisions (including equipment status up to companies in the value network).
Technology: Online information about processes in the supply chain. Therefore, interfaces are defined for equipment, technological and organizational processes, as well as for communication between entities in the value network are defined. Heterogenous systems of value chain partners interoperate.
Within the digital factory systems from the business side and technological processes are enabled for open communication. Flexible and adaptive value streams within the factory enable production to fulfill tasks more cost efficiently and keep the ability to supply goods on a healthy level. System elements, from field device to value stream, are vertically interconnected and provide a sum of (micro)-services and functions, which can be orchestrated by superordinate steering instances on each level of the factory. Thus, interoperability, open interfaces and architectures, as well as functional description frameworks are required to harmonize the services provided.
Customers and users: Shop floor personnel, factory managers/operators, domain specific
Societal: Humans in an orchestrating role regarding value streams. Humans are supported by autonomous systems.
Process: Processes are highly aligned to tactical and operative objectives. Tasks like production planning, shop floor management and asset maintenance are supported by online information.
Information: Information about current production and equipment status is available. Information about capabilities of entities is available.
Technology: Interfaces for inner company tasks are defined for any specific entity (machine/process data, business data, planning data). Autonomy of equipment is required to increase reactivity and robustness of the factory system, while maintaining safety.
Services for manufacturing or even manufacturing as a service are in focus of the scenario. New business models along the value chain of a product are enabled. For instance, equipment is not bought with a single investment, but paid for via pay per use ranging from subsystems up to whole factories. This requires availability and accessibility to information for the service provider. Platforms are available to enhance physical assets by services or entirely servitize the output of physical equipment for the customer. Understanding of physical assets over the lifetime is required from component to process level to enable economic services. Trust in capabilities of service providers and security are key requirements to enable services in this context.
Customers and users: Factory managers/operators, trading agents, responsible persons for sourcing, machinery builders, service providers, data and service specialists
Societal: Humans in a factory are involved in the basic operation of machines, while the service providers will focus on productivity and maintenance of the machines.
Process: Cost reduction for the operator of machines. Renewal of contracts is required as well as the understanding of “performing business”.
Information: Accessibility of information is given for both, service provider and factory operator. Autonomous evaluation and processing of information, like aggregation or scoring, is the base for services.
Technology: Platforms for the operation of assets from different vendors are available. The platforms enable multiple parties in offering maintenance services or operational optimization services.
Manufacturing Scenario D: Specific functionality with limited interconnectedness in a poorly digitized environment
The scenario takes a bottom-up view to the integration of function-oriented CPS, which can be found for instance in SMEs. Large systems for horizontal or vertical integration are not required in the first place. More in focus are basic functionalities for controlling physical processes on device or sub-system level of machines. Retrofit and decentral aspects require high degree of autonomy of the CPS in this scenario. Further the relevance of engineering in regard to prospective system integration, which is not necessarily seen in the situation the function is implemented. The readiness for integration of the devices has to be foreseen, at least for basic communication standards to enable subsequent integration.
Customers and users: System integrators, machine operators, SMEs
Societal: Humans are highly involved in manufacturing. Systems are used for basic visualization for human operators.
Process: Low level of digitization. Many manual processes on business and manufacturing side
Information: Information is often only available in limited scope (locally in CPS application), but interfaces are standardized for prospective integration scenarios. Sensing information is required and locally aggregated and used for autonomous decision making and control.
Technology: Smart function integration is a key for implementation. Interfaces are available.