In today’s dynamic commercial refrigeration and AC markets, contractors are faced with an ever-increasing variety and complexity of applications. Whether you’re a seasoned technician or new to the trade, you need every advantage when troubleshooting and diagnosing issues for your customers. Service technicians have access to the latest technologies in their toolkits available to them on their mobile devices.
One such tool is the Copeland Mobile app.
Access the product database
The Copeland Mobile app connects contractors to the Emerson Online Product Information database for on-the-go access to 30 years of Copeland compressor product specifications. This feature-rich app helps contractors perform the following actions in the field:
View product specification and application engineering manuals
Cross-reference Copeland products with other compressor brands/models
Quickly troubleshoot and diagnose Copeland compressors
Check the availability of local product replacements
The Copeland Mobile app is designed to give you instant access to the product, installation and service information you need to service your customers. Simply scan the barcode on any Copeland compressor to pull up its specifications or quickly find the Copeland replacement of a competitor’s model.
Connect to the industry’s largest support network
When you launch the Copeland Mobile app, you’ll immediately connect to the industry’s largest support network, comprised of more than 1,000 Copeland-authorized locations and over 600 certified Copeland technical specialists. If you have additional questions about customer service, product support or availability, representatives from our American base of operations can quickly deliver the product and technical assistance you need.
Make your job easier and our products better
While the Copeland Mobile app is designed to make your job easier in the field, it’s also contributing to the research and development of future Copeland compressors. Every time you use the Copeland Mobile app, you’re helping us contribute to a database of product and competitive information that we’re using to build better compressors.
My colleague John Wallace, director of innovation, retail solutions, and I recently partnered with the Environmental Protection Agency’s (EPA) GreenChill program to present a webinar about making the transition to an effective refrigerant architecture. In it, we discussed leading natural refrigerant systems, centralized and distributed options, and the controls schemes that support them. What follows are the key takeaways from that discussion, which you can view here in its entirety — last bullet under ‘Webinar Archives’.
Over the past decade, the transition toward natural refrigerants has been driven by a combination of dynamic market trends, which include: global refrigerant and food safety regulations, rapidly changing consumer expectations and corporate sustainability goals. This historic transition has helped accelerate the adoption and investigation of “future-proof” natural refrigerant architectures.
Regulatory drivers of transition to naturals
In the U.S., the California Air Resources Board (CARB) has not only fully implemented the now defunct EPA rules designed to limit the use of hydrofluorocarbon (HFC) refrigerants with high global warming potential (GWP), it is also actively working to enact more aggressive measures that would greatly impact future refrigeration system architectures. One current proposal under review would take effect in 2022 and mandate the following:
Systems charged with more than 50 pounds of refrigerant must use an option that is less than 150 GWP
New refrigerant sales with less than 50 pounds of refrigerant must use an option that is less than 1,500 GWP
But California is not alone in these initiatives; there are currently 25 states in the U.S. Climate Alliance which have vowed to follow its lead.
Since natural refrigerants are among a very small list of viable options capable of meeting the above criteria, the commercial refrigeration industry is likely to see an increase in system architectures designed to utilize natural options. These include centralized architectures for larger-charge systems and distributed (or micro-distributed) options for smaller-charged system types.
Leading natural refrigerants
When we think of natural refrigerants in commercial refrigeration, we are typically referring to R-744 (CO2 aka carbon dioxide), R-290 (refrigerant-grade propane) and R-744 (ammonia). Let’s look at their unique characteristics and how they can be effectively utilized.
CO2 has proved very effective in both low- and medium-temperature applications and is typically found in centralized systems such as secondary, cascade and transcritical booster. Having been successfully deployed in commercial and industrial applications in Europe for nearly two decades, it has made significant inroads in North America in recent years.
CO2 is not a retrofit refrigerant and is intended for use only in new systems. System designers, operators and technicians need to be aware of CO2’s unique characteristics, particularly its low critical point, high operating pressures and standing pressure (power outage) considerations. It has a GWP of 1, which puts it in an elite class of environmentally friendly options.
Propane continues to experience a global resurgence as a viable, efficient and very low-GWP refrigerant choice. Its high flammability has traditionally limited system charges to 150g, which is why today it’s found primarily in stand-alone systems that operate efficiently with a low refrigerant charge — such as integrated display cases often utilized in micro-distributed applications. In Europe and abroad, the International Electrotechnical Commission (IEC) recently raised its charge limit to 500g; the U.S. conservatively remains at 150g. Also, propane is not a retrofit option and is intended for new systems designed specifically for its use.
With its superior thermodynamic properties, ammonia was a logical first choice for early refrigeration systems. However, its toxicity requires careful adherence to safe application procedures to ensure operator safety and customer well-being. Traditionally, it has been used in industrial, process cooling, cold storage and ice rink applications. Most recently, ammonia has been introduced into commercial applications via cascade systems that utilize lower refrigerant charges and isolate the ammonia circuit away from occupied spaces.
System controls to support natural refrigerant architectures
Because of the unique properties in these emerging natural refrigerant architectures, system controls are even more essential to ensuring efficient operation, troubleshooting and servicing. Generally, the controls are loosely coupled to the refrigeration architecture, often following either a centralized or distributed approach.
However, the expanding variety of natural refrigeration systems can also pose new challenges for operators trying to maintain controls consistency or access a unified view across different systems. Here, a supervisory system — with its ability to integrate different devices into a common user interface — ensures that all stakeholders can quickly and easily evaluate each refrigeration system.
As regulations continue to evolve and natural refrigerant systems gain more acceptance, Emerson is prepared to help equipment manufacturers, system designers and end users utilize these very low-GWP alternatives in the development of efficient, user-friendly and economically viable refrigeration systems.
Emerson is writing a series of articles about the implications of new and transformative technologies for the commercial refrigeration industry. In our first article, I described the challenges and methodologies related to transforming a newfound wealth of data into true predictive maintenance capabilities. You can read the full article here.
One trend driving the commercial refrigeration industry’s rapid adoption of Industrial Internet of Things (IIoT) technologies is the promise of predictive maintenance. Collecting massive amounts of real-time data comes with the potential to develop data-driven algorithms that can accurately predict looming problems and failures in refrigeration systems and equipment.
In the commercial refrigeration space, operators’ goals related to predictive maintenance are to reduce energy savings, lower maintenance and service costs, improve food quality and safety (and indirectly, customer experiences), increase comfort, and reduce downtime. So as IIoT technologies become more affordable, widely deployed and interconnected, a question naturally arises: “When will we see the results of these predictive maintenance capabilities?”
It’s a fair question. After all, some industries, such as industrial automation, are seeing rapid advances in their predictive maintenance capabilities. But many of these industries also have an inherent advantage: they’re often monitoring identical devices with well-defined historical performance models, making early problem detection relatively easy.
However, commercial refrigeration is a different ballgame. Commercial refrigeration applications are diverse and complex, making the development of their predictive maintenance capabilities far more challenging. Commercial refrigeration systems consist of many diverse and interdependent components, which often originate from multiple vendors. They encompass a wide range from traditional centralized direct expansion systems to an ever-expanding array of emerging architectures designed to achieve very specific operational (and more often, sustainability) objectives. Industry trends further complicate the issue, such as the adoption of new refrigerants and the migration from centralized to distributed, self-contained and integrated systems.
These complex systems differ in the amount, type and quality of the data they can provide — making data modeling and writing algorithms for different equipment even more difficult. Add more variables into the mix, such as weather, humidity and climate — not to mention widely varying operator goals, processes and workflows — and you can start to comprehend the depth of the challenge.
Developing predictive maintenance capabilities for commercial refrigeration is not a matter of simply pouring more data into the cloud via the IIoT. That data is as diverse as the equipment and systems which produce it. Determining the predictive potential of all that data requires fundamentally changing how we understand and approach the needs of the commercial refrigeration industry.
At Emerson, we’re tackling this challenge head on, taking a methodical, deliberate approach to predictive maintenance. Our goal is not to simply throw more IIoT technologies at the challenge. We’re working to help deliver on the promise of predictive maintenance by applying our deep knowledge of the commercial refrigeration space to help operators uncover the predictive value of data gathered from many different applications. By doing so, we’re simplifying the complexities and uncovering insights into the industry’s most common refrigeration scenarios.
We’re deriving predictive maintenance solutions from IIoT data via a three-pronged methodology: 1) understand the complexity of the domain and its individual systems; 2) define what data is relevant to which situations; and 3) determine how application sensors should be used to generate the necessary data. Then we can take the crucial step of developing tools to extrapolate true predictive maintenance answers from real-time and historical data.
In upcoming articles, Emerson will expand on these learnings and provide examples of how new technology is already being used for successful predictive maintenance programs in commercial refrigeration.
Many supermarket operators face a common dilemma regarding their refrigeration systems: they know they need to make changes or upgrade their legacy systems, but they’re not sure what their retrofit options are — or even where to begin. In our next E360 Webinar, I’ll offer guidance on how supermarket owners/operators can embark on this critical journey.
Join me on Tuesday, Aug. 13 at 2 p.m. EDT/11 a.m. PDT for this informative webinar.
There’s no question that reliable refrigeration is the backbone of any supermarket operation; it accounts for more than 50 percent of the electrical consumption for an average supermarket. That’s why keeping your refrigeration system running at optimal efficiency is essential to maximizing profits and ensuring operational success.
But if you’re like many owners/operators, you’ve been relying on the same centralized refrigeration architecture for decades. During that time, these systems have typically experienced declining performance levels and energy efficiencies — all due to progressive deviations from their original commissioned states. And while these systems are perfect candidates for an upgrade or a retrofit, even newer systems can offer opportunities for improvements, especially within the context of today’s rapidly evolving industry and market dynamics.
Compared to just 10 years ago, the drivers behind refrigeration decisions have changed dramatically, and the days of a one-system-fits-all mentality are quickly becoming a thing of the past. Environmental concerns, energy costs, shifting regulations, shrinking store formats, consumer demands and omnichannel delivery have all irrevocably reshaped the supermarket landscape.
As a result, more supermarket owners/operators are reevaluating their existing (and often aging) systems while looking for any retrofit opportunities that are available to them. Our next E360 Webinar is designed with them in mind. To help you better understand the many factors to consider when evaluating a supermarket refrigeration retrofit, I’ll be discussing the following topics:
Industry and market trends driving the need for refrigeration system retrofits
How to identify deficiencies and baseline performances in centralized architectures
A look at the potential architectures of the future
Recommended technologies for retrofits and recommissioning
Energy-efficiency strategies for refrigeration, HVAC and the complete building envelope
As always, we will take time after the presentation to answer any of your questions. So, be sure to register now and add this event to your August calendar.
Emerson is applying our expertise in commercial refrigeration and AC toward building predictive models for a variety of applications and architectures, a foundation for the emerging artificial intelligence technologies in the HVACR industry. I recently discussed our work in ACHR News magazine, “The Impact of Artificial Intelligence on HVACR.” You can read the full article here.
The building blocks of artificial intelligence (AI)-enabled equipment and systems in HVACR are already well in development: next-generation sensors and controllers, increasingly sophisticated predictive analytics, and machine-to-machine learning (M2M) software, cloud data storage and the growing implementation of the internet of things (IoT). These tools are already providing opportunities to improve comfort, save energy, reduce maintenance costs and extend equipment life, all while helping end users better manage their operations.
But integrating these tools into true AI solutions — data- and algorithm-driven applications that will enable systems and equipment to learn and automatically perform critical tasks without human intervention — is a challenge that will require a deeper understanding of the complexities of equipment, HVACR architectures and building systems.
At Emerson’s innovation centers and in customer field trials, we’re tackling this challenge head on — but methodically. Rather than simply throwing more technologies into the mix, we’re leveraging our deep refrigeration domain expertise to simplify complexities and uncover insights into the industry’s most common refrigeration scenarios. We are in the process of understanding how deeply AI could be implemented into equipment and buildings, and how effectively it could help solve the industry’s biggest challenges.
As I stated in the article, Emerson is researching how some newer AI-related technologies can be utilized for more advanced services, such as detecting problems faster and pinpointing which actions need to be taken. For example, we are already incorporating some AI-related technologies into equipment when we learn they add value, such as sensors that warn of refrigerant leaks in supermarket refrigerants.
However, delivering on the promised value of AI — autonomous predictive analysis and control of HVACR equipment and even entire building environments — will require more than simply installing connected sensors and devices, transmitting clouds of data, and creating libraries of algorithms. As the automobile industry has learned, building a self-driving vehicle is a far more complex undertaking than it appears. This example is important to keep in mind when considering the inherent complexities and diversity of commercial refrigeration applications.
A typical commercial refrigeration system consists of many interdependent components — often from multiple suppliers — with potentially diverse data sources. The proliferation of system architectures and refrigerants has resulted in an ever-expanding diversity of applications. This makes data modeling and defining predictive algorithms difficult. At Emerson, we believe that the development of AI in HVACR will grow as an iterative process, via data processing performed at the equipment level — with tighter integration of sensors and controllers providing richer data to cloud- and IoT-based services. These services provide both real-time alerts and historical trends of equipment performance under a given set of conditions — including indications of potential failures.
These data sets are the foundation of the next level of AI, enabling predictive maintenance models that will anticipate problems and maintain optimum conditions across a defined range of variables. Reaching that point will require generating sufficient historical data detailing the operation, failures and problems of equipment and components. And while much of this data is available today, new sensors may also be required to provide more advanced predictive capabilities.
Relatively speaking, the use of AI in HVACR equipment and controls is still in its infancy. But we’re working to accelerate its advancement to help our industry reap its potential benefits, including: improved reliability, energy savings, prolonged asset life and, of course, predictive analytics. As more AI-related technologies arrive in the HVACR space, we’ll start to fully understand the significant benefits and valuable data they are capable of providing.
Commercial & Residential Solutions is a global innovator of energy-efficient heating, air conditioning and refrigeration solutions for residential, industrial and commercial applications. www.climate.emerson.com