Today, industrial modernization plays a significant role in how businesses move forward in what many are calling the 4th Industrial Revolution. The widespread adoption and integration of intelligent, innovative technologies in the manufacturing and process industries is driving this modern era.
For the last 10 years, several industry terms have been coined, including smart factory, Industry 4.0 and smart manufacturing. The details of each differ somewhat, but they are often used interchangeably. These terms are the stepping stones for businesses looking to modernize their processes. They each share a vision to build on the digital innovations of the 80s and 90s, including the introduction and universal adoption of computer-based industrial process and machine control systems. MESA International’s Smart Manufacturing Working Group defines smart manufacturing as “the intelligent, real-time orchestration and optimization of business, physical and digital processes within factories and across the entire value chain. Resources and processes are automated, integrated, monitored and continuously evaluated based on all available information as close to real-time as possible.”
Smart manufacturing defines a destination, but the road to get there varies depending on how current a company’s digital infrastructure is and ultimately what level of “smart” is best for them. It is clear, however, the move to an advanced level of data-driven decision making is preeminent across all industry sectors. To maintain their competitive edge, businesses must get on the smart track to modernizing their legacy systems, both from an information technology (IT) and operational technology (OT) perspective. They must also update their industrial networks to achieve a higher level of system integration.
Many facilities are at a crossroads when determining the right technological path forward. Their control platforms and digital infrastructure were installed or last upgraded in the 90s. They face hardware and software obsolescence, dwindling availability of both original equipment manufacturer (OEM) and third-party support, and a lack of internal resources with some staff nearing retirement. Under these conditions, it is tempting to rush into a system migration with the mindset of “let’s just replace what we have with the newer version.”
These replacement-in-kind upgrades usually present the path of least resistance financially and are relatively short in duration. However, they also represent a great loss of opportunity to make high-impact, insightful improvements to operations. Prior to a control system migration, it’s important to consider and understand how to take full advantage of the innovative opportunities available.
A true migration requires looking at not only the instrumentation, I/O, controllers and human-machine interfaces (HMIs), but also the data engines from which collectively we can characterize the products and process. In doing so, we can also determine how and when to make improvements, how to avoid costly unplanned downtime, and plan production and staffing more effectively, to name just a few.
Interoperability: Not So Disparate Systems
Leveraging the wealth of data available in a facility and making it accessible and usable across the enterprise is key to an effective and efficient manufacturing operation. By requiring interoperability between systems in the upfront planning process of an upgrade or migration, facilities can integrate mission-critical data throughout their processes. The term interoperability is used quite often these days when referring to OT systems and should not be confused with compatibility. In a U.S. Department of Energy presentation titled “Control System Interoperability: Can We Talk?”, they differentiated between the two terms:
- Compatibility – Two devices (or a device and a system) are compatible if they can coexist in a system (or in the same physical environment) – that is, operate without corrupting, interfering with or hindering the operation of the other entity.
- Interoperability – Two devices (or a device and a system) are interoperable if they can both work together to operate as intended, typically facilitated by an ability to share a common defined set of information. Devices share data they generate. Devices can use data generated elsewhere.
This modernization or otherwise commonly referred to as digital transformation of the production facility is the foundation on which smart manufacturing is built. However, this transformation is only possible after the supporting digital infrastructure has been put in place (e.g., the network and the connectivity to the process equipment, sensors, data storage and other supporting applications and systems). So, where do you start?
The Digital Infrastructure Journey
As with any journey, it is equally important to know your current whereabouts and where you are going – the destination. There are differing opinions on whether to begin with assessing the current state or to first define the “to be” or future state of the modernization program. Preferably, the starting point would be to develop a desired and achievable future state along with an estimated timeline to get there. This strategic goal then becomes the future state vision for the facility or enterprise.
The Future State
It is vital to approach the future state process rationally with clear and bounded business goals defined. These bounded business goals must satisfy the “achievable” precondition of the defined future state vision and will provide the basis from which the requirements for the modernization program can be built. During this process, the degree of “smart” that is to be implemented is defined and mapped out. This approach helps identify how all currently disparate systems (both IT and OT systems) will be brought together as a functional unit and provides high-fidelity information from which decisions can be made in real-time across all or some specific portion of the value chain (i.e., the full range of activities required to deliver a valuable product). Thus, the future state vision is the overarching roadmap that guides the modernization program.
It is important to note that some elements of the future state vision may become fungible during the program’s detailed definition and is typically an iterative process when mitigating the gaps between the future and current state. The vision, for example, could include migrating an existing but nearly obsolete distributed control system (DCS). It is conceivable that during the program’s current state assessment phase, it is determined the existing DCS’s OEM has an upgrade path, which would ensure deploying a phased approach. This would allow the cost to be spread out over a longer time period, while also affording the functionality to fulfill the connectivity, data acquisition and data exchange requirements (interoperability) to support the future state vision.
The opportunity here is for the organization to look at implementation in terms of time increments that make sense down the road; for instance, it could be two years, five years, or more likely a phased implementation over the course of several years. This timeline will be dependent on the overall breadth of the project. It may, for example, encompass the following tasks:
- A redesign and implementation of the plantwide network to support enhanced bandwidth, wireless connectivity, reliability and security
- A control system upgrade or migration
- Process historian upgrade or migration
- The addition of IIoT devices for increasing the availability of process data and as mobile operator interfaces
- Adding advanced process control (APC), if applicable
- Adding or upgrading a manufacturing execution system (MES), an enterprise asset management/computerized maintenance management system (EAM/CMMS), a quality management system/laboratory information system (QMS/LIMS), an enterprise resource planning (ERP) system or a combination of them all
- A broad expansion of the interconnection of process data with current and new business systems
- Adding advanced analytics to provide the necessary context to the additional wealth of process and business data that will be a strategic result of the modernization program
Assessing the Current State
Once a vision for the future has been laid out, it is time to determine the current state of the digital infrastructure (e.g., hardware, software, IT / OT platforms, networks and data availability and integration):
- How well does it all really work?
- Is it just past its prime, or is it completely obsolete?
- What portion of our manual processes are just workarounds to make up for shortcomings in the existing systems?
Next, determine what gaps exist between the current and future states and then determine what is required to address the gaps and how much it will cost. It is also important to revisit the requirements (future state vision) to determine if changes must be made to accommodate budgetary or scheduling concerns. The ultimate outcome of this process will be the scope, schedule and budget for the program’s detailed engineering phase.
Assembling a Team
At the outset of the modernization program, a cross-functional team will be identified. Because of the broad reach that this type of program has, the team would be comprised of members from each discipline involved. At this time, it is also necessary to determine if it would be beneficial to engage an engineering and technology partner to assist in the process. A neutral third-party partner who possesses a broad base of experience in defining and implementing modernization programs across multiple industries and platforms is key. They can serve as both a facilitator and advisor in the definition and assessment phases. An experienced and innovative partner can also apply the engineering rigor to lead the detailed design phase, identify and vet potential hardware and software solutions, produce accurate estimates on designing and implementing the new systems all while bringing to bear best practices from a wide spectrum of industries.
Once the team is assembled, each member should have clearly defined roles and responsibilities. It is also necessary to establish a communication plan and identify the deliverables and a schedule. A common tool used to define, document and communicate this process is a RACI (responsible, accountable, consulted and informed) matrix. Employing an agile framework (e.g., SCRUM) for the definition and assessment phases is very effective for managing the team and deliverables.
Modernization’s Many Facets
An industrial modernization project to digitally transform IT and OT systems is a broad topic and covers many technical aspects. The infrastructure required to support the transformation also has many facets – too many to go in-depth here. What’s important is to realize that every facility is different and there is no one-size-fits-all, out-of-the-box solution.
With so many solutions to consider, a sure path to disappointment and possible failure would be to begin the process with a predetermined solution and molding the functional requirements to match the system/platform capabilities. Instead, it is critical to a modernization program’s success that a team is assembled, and a project methodology adopted. Using the methodology to manage the definition process, the team can accurately and completely define the functional system (and/or upgrade) requirements to achieve the future state vision. Thus, potential technological solutions can be evaluated on an “apples-to-apples” basis with respect to the requirements and lead to a higher level of system integration and future success.