Most industrial organizations today still do not fully understand cloud computing, cloud security, or the applicability of the cloud to the industrial environment. ARC Advisory Group often hears talk about “migrating to the cloud.” However, cloud computing is not a destination to which to migrate or store data, but an enabler for business transformation. A cloud business approach takes advantage of the global and parallel nature of cloud computing. Companies that understand this can innovate and transform.
Cloud computing enables agility and innovation by providing organizations with global access to data and the flexibility to employ software applications of their choice. Cloud computing-enabled software-as-a-service (SaaS) can also support concurrent engineering to optimize design and compress project schedules, plus reduce upfront software expenditures and ongoing support costs to a significant degree.
With the emergence of Industrie 4.0 and Industrial IoT, cloud computing services companies and engineering and industrial software companies have a tremendous opportunity to change the game for engineering. For example, Microsoft and AVEVA have collaborated to shift the deployment model for engineering simulation tools for design and operations. The objective here is to increase security and reduce reliance on IT service organizations, ultimately putting more control into the hands of engineering organizations. This transforms simulation into a higher-value agile service, provides a transition for legacy software, and allows users to retain invaluable intellectual property (IP) for engineering. The ubiquitous nature of cloud computing shifts procurement of software and solutions from central IT to the engineering operations groups to better support Industrie 4.0 and Industrial IoT approaches and strategies.
Engineering Operations Organizations Can Now Procure Software-as-a-Service (SaaS)
Within many industrial organizations, the IT group has traditionally been responsible for and has control over procuring, deploying, and supporting engineering software. While IT still has an important role in planning the technology investment stack to secure and sustain IT solutions for a multitude of internal customers across the enterprise, the move from the private cloud to public SaaS model in the technology stack diminishes this role to a significant degree (see figure 1).
NIST defines software as a service (SaaS) as a capability provided to the consumer is to use the provider’s applications running on a cloud infrastructure. The applications are accessible from various client devices through either a thin client interface (such as a web browser) or a program interface. The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings. SaaS typically involves the sale of a service provided over a period of time. Generally, in a software licensing arrangement, the customer obtains rights to use the software on its own computers.
In the past, over-burdened IT groups often could not accommodate the specific priorities and agility requirements of the business units. IT priorities are often strongly influenced by demand in areas such as finance, network infrastructure, and other ancillary IT services. The rigorous IT Demand Management process defined by the ISACA (Information Systems Audit and Control) standards organization aims to understand, anticipate, and influence customer demand for services. This process works with the Capacity Management process to ensure that the service has sufficient capacity to meet the required demand for particular services. Cloud computing changes this. Business units can now externalize IT services. What, in the past, was a service under “care and control” of internal IT, is now performed by vendor-managed services as a SaaS application.
The IT function can be reduced to resolving simpler problems and, if required, managing interfaces. Business units can now procure software as-a-service on cloud-based infrastructure from companies like Microsoft to reduce demand on internal IT services, simplify problem resolution, and (if required) manage interfaces. For this deployment model, these applications are delivered as a SaaS model. The SaaS model commoditizes the IT datacenter, making many IT services superfluous. SaaS applications change the business and IT relationship completely, reducing the load on IT groups and enabling engineering departments to focus on mission-critical engineering design and optimization activities.
In the past, IT roles would encompass all services, often leaving business units out of critical decisions and key processes. Increasingly, more of what was previously done by internal IT or IT shared service organizations will be done by business units (see figure 2). This is the essence of IT to OT (operational technology) convergence. This means that engineering organizations will procure their own technology using SaaS models.
The IT role can then focus on overseeing and optimizing critical shared services across the enterprise and overseeing business services strategy and architecture. Managing technology procurement and integration still requires leadership, but this leadership is likely to be provided by someone reporting to the head of business services. This IT-OT convergence brings a stronger focus on the application of technology and operational efficiency or cost saving throughout the business.
Engineering Organizations Recognize the Importance of SaaS
Leading process industry users recognize the importance of SaaS models and how much of the IT services (networks, storage, provisioning etc.) has been commoditized. These users adopt a project culture focused on “try fast, build fast, fail fast,” helping users deliver the value of Industrie 4.0 with greater agility. Industrie 4.0 may enable the value propositions associated with predictive maintenance, on-demand training and simulation, or process optimization and “what-if” analyses. Some also realize that adopting standard best practices for engineering applications is an important part of digital strategy, since it can help avoid costly and unnecessary customization. Many also recognize that the SaaS delivery model is both typically more secure and faster to deploy than the legacy on-premise model.
Industrie 4.0 and digitization initiatives can drive strategy away from central IT organizations. For engineering organizations, SaaS models help decouple the sometimes-over-complicated IT Demand process to help increase agility. Process industry leaders can choose an external third-party to help with their Industrie 4.0 agenda but may also give the internal digitization organization (or IT) the first chance, especially if there is an opportunity to use an IT-provided platform. SaaS models from SaaS providers are particularly attractive for engineering Industrie 4.0 programs. Typical metrics for an Industrie 4.0 program include:
- Accelerator projects have success criteria defined
- Financial results (NPV) are key measures
- Businesses sign off on value to be delivered
- Responsiveness to opportunities and how quickly project teams move between stage gates
SaaS Changes Engineering Simulation Forever
A few decades ago, IT professionals began to use the term “service-oriented architecture” to describe the assembly of many web-based user interfaces for desktop applications. Usually, the deployment model was to set this up in an internal data center or in servers rented from a third-party-hosted solution. Today, the situation is very different, with SaaS deployments becoming increasingly important. A SaaS software application is built specifically for cloud computing and virtualization environments. SaaS applications are designed, developed, and deployed to reap maximum functionality and services from a cloud computing and virtualization infrastructure. Although SaaS applications might be like conventional software applications, the back-end computation, scalability, and parallel processing are compatible with and support a cloud infrastructure. SaaS applications have the following characteristics:
- Massively parallel: The application incorporates parallelization techniques within task execution and data storage.
- Complete utilization of cloud resources: The application should use infrastructure (Azure or AWS or other infrastructure vendor) APIs and other procedures to simplify tasks and use most or all available resources.
- Cross-cloud paradigm: The application should be easily migrated and deployed within multiple cloud providers.
- Supports business models; multi tenancy, automatic updates; self-service applications; scalability and volume of users.
AVEVA’s Approach to Agile Engineering Using SaaS Applications
To date, only a handful of industrial software companies have recognized the importance of and the suitability of the SaaS model for engineering simulation software. AVEVA, for one, has joined forces with Microsoft to lift its flagship engineering simulation and operator training simulation software into a SaaS environment. AVEVA’s PRO/II Process Engineering, DYNSIM Dynamic Simulation, and Operator Training Simulation software solutions, with their unique approach using containers and virtualization can now be run on-demand across the globe. On the AVEVA Engineering & Training Cloud, the engineering subject matter expert can experience a new workflow and user experience. This leverages the respective strengths of both AVEVA and Microsoft to transform simulation to a higher-value agile service, provide a scalable web-access for legacy software, and allow users to retain invaluable intellectual property (IP) for engineering. In the near future, this will expand to include enterprise-wide training, leveraging dynamic simulation with augmented and virtual reality to deliver enhanced training solutions applicable to everyone in the corporation. According to AVEVA, this integrated solution:
- Provides ubiquitous infrastructure, enabling engineering users to run simulations at any time, location, or on any device
- Doesn’t require long IT upgrade and computer refresh cycles to enable users to leverage the latest engineering software features and capabilities
- Provides all the benefits of engineering software, but without the overhead of installation, deployment, version control, and hardware maintenance
- Makes it easy to deploy models securely to allow users to share engineering models with authorized partners and suppliers
- Enables engineering users to begin optimizing design right away without having to develop special skills
- Increases engineering design agility
The differentiator introduced in Microsoft and AVEVA technology is the ability to lift flagship, non-SaaS software (even software written in Fortran or other old programming languages) to have implied SaaS values. This technology can be used for both AVEVA applications and complementary third-party applications.
The cloud deployment approach can also accelerate the engineering process, from the initial design feasibility performed by the engineering and procurement contractors (EPCs), through front end engineering design, detailed design, installation and commissioning, and – ultimately – through operations and decommissioning.
The transformational opportunities presented by Industrie 4.0 (often referred to as the fourth industrial revolution), motivate engineering organizations to rethink work processes and the use of engineering tools and how they each support objectives to design with greater agility.
This is increasingly important in today’s process manufacturing environment in which variability in both feedstocks and energy costs demands unprecedented agility. The loss of process, process control, and operations and maintenance knowledge and expertise creates additional challenges that cloud-enabled engineering design solutions such as those that AVEVA and Microsoft have teamed up to provide can help.
In the past, depending on the project phase (conceptual design, detailed design, startup and commissioning, process optimization, etc.) and responsible party (process licensor, EPC, owner-operator, etc.) a variety of different engineering tools were typically employed to support either steady-state or dynamic simulation. In most cases, each of these tools had different models for process simulation, different data entry requirements, and different data and human interfaces. This increased engineering effort, complexity, and cost and inhibited agility. It also prohibited effective use of concurrent engineering, which can reduce costs and help compress project schedules.
The “platforming” or IT-OT convergence of process engineering simulation tools helps engineers create reusable workflows and automate data authoring in a broader platform for simulation. The new work processes created enable people to focus on more value-adding activities and shortens the time needed to design and optimize by moving from sequential to simultaneous engineering. “Re-platforming” will happen much faster in the cloud.
Process engineering plays a key role in the Industrie 4.0 vision for the process industries. Industrie 4.0 is defined as “the transformation of industrial products, operations, value chains, and aftermarket services that are enabled through the augmentation of people and knowledge, through the expanded use of sensors, data and analytics.” This vision has reshaped the role of process engineering and the associated simulation tools.
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Keywords: Process Engineering, Simulation, SaaS, Cloud Services, Cloud Computing, Agile, Industrie 4.0, IT Services, AVEVA, ARC Advisory Group.