IT in Manufacturing


Energy management software

October 2018 IT in Manufacturing

Poorly designed and overly simplistic energy performance indicators (EnPIs) often drive energy savings at the expense of product yield or quality. However, a well-designed energy management information system (EMIS) can minimise energy cost without impacting production and, in some cases, can even enhance process performance.

Traditional energy monitoring applications mainly focus on improving energy-side key performance indicators for fired boilers and heater efficiencies, energy intensity, utilities’ marginal cost, etc. These monitoring applications rely on inputs from various process measurement instruments with temperature leading the way, to verify performance.

However, covering an expanded range of production parameters – including energy supply, demand and recovery, product quality and process yields – requires integration of the process with energy simulation, monitoring and optimisation tools. This article shows how to overcome traditional barriers to energy saving by using rigorous process simulations to monitor performance and determine optimum operating targets for improving both energy and process performance.

The energy opportunity

Energy is the largest controllable operating cost at most process plants. A typical refinery or petrochemical plant may spend $200-300 million/y on energy, so cutting just 3% in energy cost can save $6-$9 million/y. Such energy savings always result in direct bottom-line benefits, unlike adding capacity or changing product mix, which depend on anticipated market conditions.

Energy production and distribution systems often constrain processes. For example, a process compressor can be limited by its turbine drive’s capacity and efficiency, so steam and condenser operating conditions or degradation of the turbine can mean the drive reaches its limit before the compressor does. In another example, the amount of heat a process furnace is able to deliver can restrict unit throughput. Energy-related bottlenecks often curb throughput of high-margin processes by 2-3%.

One challenge is to understand the amount of potential energy improvement. Plants typically compare themselves against their peers. However, this comparison is only meaningful if the leaders are highly efficient.

An alternative approach is to compare energy use against a thermodynamically and economically achievable minimum. KBC Advanced Technologies, a wholly-owned subsidiary of Yokogawa Electric Corporation, has developed an energy metric called the Best Technology (BT) index. The target BT index is calculated based on an optimised process configuration including reactor conditions, number of distillation column trays, etc., as well as pinch analysis for heat recovery and R-curve analysis for utility delivery. This enables the specification of all equipment for maximum efficiency.

Pinch analysis is a methodology for reducing energy consumption of processes by calculating thermodynamically feasible energy targets. R-curve analysis determines the hypothetical ideal utility system and fuel utilisation for power and steam generation.

Repeating these optimisation calculations for a range of feedstocks, operating severities and product yields determines a relationship between optimum energy use and process performance. The optimum target energy benchmark is defined as 100.

The actual BT index is calculated as the ratio of actual energy use divided by the target, in %. For example, if the plant is using twice the energy of the benchmark, then its BT index is 200%. This index basically compares current energy use against that of the best available technology in the market.

EMIS issues

Most EMIS software packages focus only on the energy supply side (for example, the efficiency of production of steam and power for use in the process), so their EnPIs do not reflect the impact of feedstock effects or process yield. For instance, if energy consumption increases, they cannot indicate whether this stems from inefficiency, lower quality feedstock or the demands of higher quality products. These software packages may monitor equipment performance but often miss the chance to switch an item of equipment off when its output is not needed to support production.

EMIS software can become out of date and may get misused, and plant personnel may fail to exploit its full value. Consequently, sites do not always act upon advice and recommendations provided by the EMIS because it is not seen as irrelevant.

An EMIS frequently does not address the interaction of energy and production yield. Many plants integrate their energy systems with production processes, so changes in one area impact other areas.

Complicating the problem are changes in staffing, particularly the loss of veteran staff and the push to adopt leaner operations, making it more difficult for work processes and practices to catch up with technology.

Nevertheless, many companies still use a traditional EMIS approach. This produces energy cost savings but can miss some opportunities by not considering the combined effects of energy use and process performance.

An improved approach

Adding process considerations can solve EMIS problems. For instance, simplified EnPIs drove the wrong behaviour in a fluidised catalytic cracker (FCC) at a refinery. In this FCC, an opportunity existed to lower cooling water temperature by resolving an issue on the cooling towers. This colder cooling water would improve condenser vacuum and increase the efficiency of a condensing turbine, providing benefits in one of two ways:

1. Reducing steam demand and saving energy.

2. Debottlenecking the compressor being driven by the condenser.

Conventional EMIS calculations for option 1 show a small savings of steam, amounting to $80,000/y, by improving the standard EnPI metrics of total energy use and specific energy consumption.

For Option 2, the EnPIs of total energy use and specific energy consumption increase, driven mainly by higher coke burn. However, when corrected for the improved process performance, the BT index decreases. Profitability is dramatically better, with more than $10 million/y increased value. The BT index is aligned with the yield drivers and, therefore, will not penalise profit optimisation.

In this example, a single simulation platform with an integrated process and energy model performed the optimisation to generate operating targets, considering both energy and yield. The resulting targets were embedded in the EMIS optimiser software.

Update your EMIS

Today, plants face a compelling need to reduce energy costs and improve yields without extensive and expensive equipment modifications, while ensuring energy enhancements do not adversely affect process performance, and ideally improve it.

Improvements needed in EMIS software to address these issues include:

• Process simulation to monitor performance and determine optimum operating targets by considering both energy and process performance.

• Updated EnPIs with well-defined targets to track energy performance in a consistent way while minimising feedstock and yield effects.

• Site-wide energy management and optimisation of utilities to deliver results and recommendations to the right people at the right time.

• Cloud-based support from the EMIS vendor to provide performance management and expert troubleshooting to resolve complex issues in real time.

Initial results of such an integrated approach show benefits can be substantial, ensuring Yokogawa and KBC are ideal partners for energy management solutions and services. Achieving 3-10% cuts in energy consumption or carbon emissions is often possible without capital investment in new equipment. Where energy systems are constraining process performance, sites have realised 1-3% increases in throughput or yield, with the synergy between process and energy optimisation leading to benefits far greater than considering either in isolation.

For more information contact Christie Cronje, Yokogawa South Africa, +27 11 831 6300, [email protected], www.yokogawa.com/za



Credit(s)



Share this article:
Share via emailShare via LinkedInPrint this page

Further reading:

Looking into the future of machine vision
Omron Electronics IT in Manufacturing
Artificial intelligence (AI) is driving a significant transformation in all areas of industrial automation, and machine vision is no exception. Omron’s AI-powered machine vision systems seamlessly integrate state-of-the-art algorithms, enabling machines to analyse and interpret visual data meticulously.

Read more...
Driving digital transformation in the truck industry
Siemens South Africa IT in Manufacturing
Tatra Trucks, a leading truck manufacturer in Czechia, has adopted the Siemens Xcelerator portfolio of industry software including Teamcenter software for product lifecycle management and the Mendix low code platform to help increase production volume and strengthen its ability to manufacture vehicles that meet specific customer requirements.

Read more...
Opinion piece: Digital twins in manufacturing – design, optimise and expand
Schneider Electric South Africa IT in Manufacturing
Digital twin technology can help create better products, fast. It can also transform the work of product development. This strong statement from McKinsey reinforces how far digital twins have come in manufacturing.

Read more...
Asset tracking is key to driving operational excellence and sustainable growth
Schneider Electric South Africa IT in Manufacturing
Asset tracking plays a critical role in the success of industrial businesses. By effectively managing and monitoring assets, companies can optimise their operations, ensuring that resources are used efficiently. This leads to improved productivity and reduced costs.

Read more...
Siemens democratises AI-driven PCB design for small and medium electronics teams
Siemens South Africa IT in Manufacturing
Siemens Digital Industries Software is making its AI-enhanced electronic systems design technology more accessible to small and mid-sized businesses with PADS Pro Essentials software and Xpedition Standard software.

Read more...
Predicting and preventing cyber-attacks with AI and generative AI
IT in Manufacturing
The speed at which cyber threats are evolving is unprecedented. As a result, companies need to implement state-of-the-art technology to protect their data and systems.

Read more...
Real-world lessons in digital transformation
IT in Manufacturing
Synthesis has helped businesses across multiple industries with their digital transformation by solving their unique integration challenges.

Read more...
Enhancing cyber security for industrial drives
Siemens South Africa IT in Manufacturing
The growing connection between production networks and office networks as part of IT/OT integration and the utilisation of IoT have many benefits for industrial companies. At the same time, they also increase the risk of cyber threats. Siemens ensures that your know-how and plants are protected at all times.

Read more...
Immersion cooling systems for data centres
IT in Manufacturing
The demand for data centres in Africa is growing. The related need for increasing rack densities brings with it escalating cooling requirements.

Read more...
Transforming pulp and paper with automation and digitalisation
ABB South Africa IT in Manufacturing
The pulp and paper industry in South Africa is undergoing a significant transformation from traditional manual processes to embracing automation technologies. Automation in pulp and paper mills aims to improve various production stages, from raw material preparation to final product creation.

Read more...