In today’s smart factories, cyber physical systems monitor physical processes, create a virtual representation of the physical world, and even make decisions. The traditional structure of the automation pyramid and the distinction between information and operations technologies are blurring. Cyber physical systems enable new means of communication and cooperation among devices, production assets and information systems in an orchestrated and decentralized way in real time. Via the Internet of Services, both internal and cross-organizational services are being used throughout the value chain.
Different countries and regions have designed their own programs to achieve this fourth industrial revolution. For example, the German government and the European Union promote the Industry 4.0 program, while in the United States, the Smart Manufacturing Leadership Coalition (SMLC) is the main initiative. Other countries, such as Japan and Korea, have also established national programs on smart manufacturing.
Focusing on Europe, in 2016, the European Commission started the Digitizing European Industry initiative (DEI) aimed at reinforcing the EU’s competitiveness in digital technologies. The European Commission strategy defines four pillars: digital innovation hubs, a regulatory framework, skills development and digital platforms. In its Horizon 2020 program, the EU launched several initiatives to advance the development of digital industrial platforms like DT-ICT-07 2018–2019 and 2019–2020 with a budget of more than 100 million euros.
Digital platforms for manufacturing play a key role in addressing competitive pressures and integrating new technologies, apps and services. The challenge is to make full use of new technologies that enable manufacturing businesses, particularly mid-caps and small and medium-sized enterprises to meet the requirements of evolving supply and value chains. Besides innovation and research actions, there are also coordination and support activities to cross-fertilize the industrial platform communities, facilitating the adoption of digital technologies from ongoing and past research projects to real-world use cases and encouraging the transfer of skills and know-how between industry and academia.
The digital manufacturing platform scenario is complex and uncertain, as the main players and roles are still being shaped. Trying to foresee market scenarios, in December 2016, The Economist compared two platforms, General Electric's (GE) Predix and Siemens' Mindsphere, to evaluate the likelihood of one finally dominating the industrial Internet. It found that it is unlikely that a single platform will reach complete dominance and highlighted the significance of an open strategy.
IoT Platforms
An IoT platform is middleware between IoT devices and IoT gateways on one hand and applications on the other hand. Also known as an application enablement platform, an IoT platform enables the building of applications. The essential capabilities of an IoT platform are connectivity and network management, device management, data acquisition, security, event processing, monitoring, analysis, visualization, integration, storage, and application enablement.
There are several vendors with different architectures, ways of connecting and managing IoT devices, methods of managing and analyzing data, capabilities for building applications, and options to leverage IoT in a meaningful way for any given use case—consumer applications, enterprise IoT applications, and Industrial IoT or Industry 4.0. In the end, IoT is part of an integrated approach to leverage data from devices and assets. There are hundreds of players in the market, and although IoT platforms have many functions in common, there are differences in the offerings with sometimes very different features.
Here are the main players in the IoT platform market:
Microsoft Azure IoT offers device monitoring, rules engine, device shadowing and identity registry. Upon these basic services, Azure IoT incorporates several existing products, such as stream analytics, Power BI (data visualization software), IoT hub, notifications hub, and some prepacked machine learning. In addition, Azure Digital Twins allows engineers to create digital models of any physical environment, including places, things and people.
Oracle IoT Cloud Service is a managed platform-as-a-service (PaaS) cloud-based offering that allows engineers to connect devices to the cloud, analyze data from those devices in real time, and integrate data with enterprise applications, web services, or with other Oracle Cloud Services, such as Oracle Business Intelligence Cloud Service.
Google Cloud IoT Core is a fully manageable IoT platform. This platform is marketed as a major rival of the other platforms, since it mainly concentrates on intelligence. To achieve this intelligence, it employs ad-hoc queries using Google Big Query and Cloud Functions workflows. Thus, the devices can automate changes based on real-time events; data visualizations are done using Google Data Studio; and machine learning is done with a cloud machine learning engine.
IBM Watson IoT is a cloud IoT platform that connects devices and IoT device data into a repository that engineers can use to gain insights to improve their operations and even launch new business models. Users receive real-time data exchange, data storage, device management and secure communications.
AWS IoT Core is a cloud IoT platform that helps turn cars, turbines and other systems into “smart” objects by connecting and managing sensors on these objects. AWS IoT Core provides a secure device gateway, device shadows, a device software development kit, a registry for recognizing different devices, a message broker, and rules engine that evaluates inbound messages.
Bosch IoT Suite is a cloud platform with services designed to meet the requirements of every IoT project. The platform was initially designed and built to provide IoT solution developers flexibility and ease to perform their daily tasks.
All these platforms are large, generic IoT cloud platforms from software and technology vendors. However, many telecommunications vendors, including AT&T, Telefónica and Vodafone, also offer IoT platforms.
Digital Manufacturing Platforms
In the early stages of the digitization of manufacturing, machinery OEMs offered remote machine monitoring systems (RMMS)—software designed to allow customers to monitor their shop floor equipment. DMG Mori Seiki has been a pioneer with an RMMS called Mori Net that allowed customers to monitor DMG machine tools over a local network or the Internet. For non-DMG machines, the company developed separate software, called Messenger, based on MTConnect, a standard for accessing machine tool data.
The advent of the Industrial IoT pushed the adoption of sensor-based information collection to address machine downtime and process delays. In this way, machine monitoring has evolved into condition monitoring. To achieve this goal, data acquisition systems and data loggers are used to monitor all kinds of industrial equipment and devices.
Besides condition monitoring, more types of services and requirements, such as preventive maintenance, run-time and uptime measurement, energy monitoring and performance tracking are being introduced. As a result, digital manufacturing platforms are being shaped to cover a broader scope.
The European Factories of the Future Research Association (EFFRA) is a nonprofit, industry-driven association that is performing an important role in the digitization of manufacturing and the development of digital manufacturing platforms. For example, the “Connected Factories” project establishes a structured overview of available and upcoming technological approaches and best practices. The project identifies present and future needs, as well as challenges, for manufacturing industries. Connected Factories explores pathways to digital integration and interoperability of manufacturing systems and processes and the benefits this will bring. The project will enhance awareness of digital technologies in manufacturing, but also provide expertise to make informed choices about technology and business models.
Digital manufacturing platforms allow the provision of manufacturing services in a broad sense. Digital platforms provide services that can be used for data collection, storage, processing and delivery. These data describe the whole context, which includes the product being manufactured, the processes, the production assets, the workers, and the entire value network. A digital platform for manufacturing can provide a digital extension of functionalities for physical assets through the adoption of information and communication technologies. All services are aimed at optimizing manufacturing from different perspectives, such as efficiency, availability, quality, performance and flexibility.
Digital platforms can be on premise, in the cloud or a hybrid of the two. Either way, a prerequisite for widespread adoption in a productive environment is the need for agreements on industrial communication interfaces and protocols, common data models, semantic models and the interoperability of data. RAMI 4.0 is a framework that will help accomplish this task. RAMI 4.0 is a three-dimensional layer model that compares the life cycles of products, factories, machinery or orders with the hierarchy levels of Industry 4.0. The model divides existing standards into manageable parts, integrates different user perspectives, and provides a common understanding of Industry 4.0 technologies, standards and use cases.
Digital Platforms as Ecosystems
A digital manufacturing platform is part of a layered architecture that integrates a set of functions or software services that can be implemented by different technologies using interfaces and making the data available to be consumed by third party applications. For example, a platform could make available operational state and machining process data provided by a machine tool to be used in business intelligence applications that provide production or overall equipment efficiency insights. Platforms can be understood as operating systems that offer a set of applications as services. These services make shop floor data (from machines, products and operators) accessible to other software applications, such as production planning, operation and process, quality management, maintenance, troubleshooting and energy management. The services will be exposed using information technology open-standard interfaces, such as API Rest, or operations technology standards, such as OPC-UA. This way, an ecosystem of application developers can be fostered.
A digital manufacturing platform includes three characteristics. First, there is a community aspect that embodies an ecosystem of users in a social network connected to each other. Some users are service providers. Their raw material is data, and their products are usually software apps for value-added data-driven service. Value creation relies on a solid technology infrastructure.
Infrastructure is the second aspect. This aspect of a digital manufacturing platform is to enable users and partners to develop apps and create value added data-driven services. The ability to develop and deploy software apps in the platform is a core issue to grow an ecosystem of data-driven service consumers and producers. As a result, it must be an open infrastructure that is able to integrate and unlock technologies and systems.
The last aspect is the data role. Data is the raw material of digital manufacturing platforms, provided by enterprise management systems, industrial assets, devices and sensors. It must be exchanged, accessed and processed in a proper way.
The ecosystem of digital manufacturing platforms consists of four types of players. These are the platform owners, who are in charge of governance; the providers, who are the interface with users; the producers, who create the offerings; and the consumers.
With data gaining in importance for global value creation, the International Data Spaces Association (IDS) is devoted to forming a basis for data ecosystems and market places based on the principles of trust and data-sovereignty. Data creators must have control over who is using their data, for how long, for which application, how many times, and according to which terms and conditions.
Digital Platforms From the R&D Perspective
In Europe, digital manufacturing platform initiatives have been fostered by public-private partnerships. Factories of the Future (FOF) and Sustainable Process Industry through Resource and Energy Efficiency (SPIRE) are two such partnerships that explicitly address digital platforms for discrete manufacturing and the process industries, respectively.
Under FOF, 10 projects and one coordination and support action, called “Connected Factories,” were started in 2016 to develop reference implementations of platforms in a multisided market ecosystem. These include user-driven proof-of-concept demonstrations and validation in several different scenarios. Six projects focused on digital platforms for factory automation (Auroware, Disrupt, Daedalus, Faredge, Safire and Scalable4.0), and four focused on supply chain and logistics (Composition, Digicor, Nimble and VF-OS).
Digital Platforms From Equipment Suppliers
In addition to efforts by IT vendors, industrial conglomerates, and R&D initiatives, machine tool builders are aiming to transform their businesses digitally. By using data obtained from their machine tools in the field, OEMs can develop predictive and prescriptive products for their customers, improving machining performance, health and safety, energy-efficiency and business domain integration. These products include software for HMIs, production management, machine and shop floor monitoring and technical assistance.
Machine tool builders are investing more and more in digital platforms to provide comprehensive systems for their customers.
DMG Mori is a pioneer when it comes to digitization in machine tool construction. DMG started with CELOS, an operating and control system based on applications. Supported in ADAMOS, CELOS can become an open network and a digital market for the machine construction industry.
Relying on Microsoft Azure infrastructure, ADAMOS was founded as a strategic alliance for Industry 4.0 and the IIoT. ADAMOS stands for ADAptive Manufacturing Open Solutions. ADAMOS is the first alliance of global market leaders in mechanical and plant engineering. It was founded in 2017 by DMG, Dürr, Zeiss, ASM PT, Software AG, Karl Mayer, Engel Austria and PwC Germany.
Machines from the Homag Group have been connected to the plant level for a long time. They even have their own MES system. They started with their own digital platform that connected them to the cloud. Now, it is an open platform, called Tapio, integrated in ADAMOS.
Trumpf’s smart factory platform, Truconnect, includes a comprehensive portfolio of consultancy, software and hardware resources. Trumpf’s subsidiary, Axoom, provides a cloud monitoring platform for the company’s machines, but it is not exclusive to competitors.
Bosch Connected Industry bundles software and services for Industry 4.0 in a comprehensive portfolio called Nexeed.
Siemens machine tools are, of course, compatible with the company’s Mindsphere software, which runs on top of Microsoft Azure or AWS infrastructures.
FIELD (FANUC Intelligent Edge Link & Drive system) is FANUC’s open platform system. It gives machine tool builders, robot manufacturers, and sensor and peripheral device manufacturers the freedom to develop their own applications. FIELD connects each device within a factory, but also allows the flexibility to connect to upper host systems, such as enterprise resource planning, supply chain management and manufacturing execution system software.
Schaeffler focuses its products in the digital world. Schaeffler has incorporated sensors, actuators and control units with embedded software. As a result, it is possible for these components to collect and process data on the condition of a machine and then convert this data into added-value services. With IBM as strategic partner, Schaeffler provides a digital platform for processing large amounts of data, generating valuable insight to transform operations. The Schaeffler cloud is a platform for engineers to securely and reliably access data from their machines.
Conclusions
The development of digital manufacturing platforms is still in an early stage, but supported by a mature IoT ground. Due to the broad scope of the concept, it has required the definition and development of a reference implementation, RAMI 4.0. In the current platform building context, it is not a matter of making choices for platform adopters, but planning an incremental roadmap towards digital transformation. In this sense, the openness of the technological architecture is a must, where state-of-the-art technologies for IoT, artificial intelligence, robotics, cloud or Big Data can be reused and integrated with interfaces described via open specifications. Platforms should aim for openness, avoiding lock-ins, preventing dominant positions of individual players, and compliance with standards and regulation.
It is remarkable that the role of the major infrastructure-as-a-service providers is becoming more and more vertical or domain-oriented. The role of big players, such as Amazon or Microsoft, has been the provision of IoT and IT infrastructures with pay-per-use business models so far. Now, these players are moving towards platforms-as-a-service in manufacturing. This movement is being carried out accompanied by reference OEMs of prioritized industrial sectors.
In spite of the advances achieved so far, there is still a lot to do to connect to additional services in true plug-and-play fashion. Ultimately, developers will need to consider:
- the multisided ecosystem of service providers, platform providers and manufacturing companies.
- mechanisms for the commercial or open-source provision of the digital services through appropriate marketplaces.
- modularity of existing or in-development platforms covering different “regions” of the RAMI framework.
- legacy system integration.
- semantic barriers.
- requirements of specific manufacturing sectors.
The benefits of the fourth industrial revolution must be monetized for companies, to the extent that technology advances become reality. The definition and support of new business models based on data will be the next big challenge in relation to digital platforms. All these issues outline future work in digital manufacturing platforms.
