Plant Management
With the rising cost of energy and stringent environmental regulations, companies are increasingly focused on improving energy efficiency. The cost of power and utilities is often the largest controllable operating expense after the purchase of raw materials at most large operating sites. ROMeo Utilities Optimisation software automatically, and
in real-time, optimises its energy supply within the context of changing economic and plant needs and environmental constraints. It is especially attractive for plants that have varying energy prices or the changing possibilities to buy, produce or sell power. The solution can result in significant reductions in
energy cost, with a typical payback in 6-12 months or less. Key benefits include: a 3-5 per cent reduction in energy consumption; ability to reduce carbon dioxide, SOx and NOx emissions; automatically takes advantage of off-peak power pricing; optimises fuel type, boiler and turbine load distributions; and better fuel gas management with fewer alarms. The solution is capable of rigorously modelling all components of a typical industrial utility system including turbines, boilers and power distribution systems. Its patented graphical scheduling system enables automation of data gathering, model execution and reporting. Other capabilities include integrated data reconciliation and identification of faulty instruments. In addition, when used with Wonderware Intelligence, it is possible to develop key performance indicators for energy costs and operational impact. Recently Invensys also added to its plant optimisation
offerings with a new solution that complements its existing portfolio of SimSci-Esscor hydrocarbon processing industry (HPI) offerings. To help refiners meet the increasing demands of today’s operating environment, the company has issued two new offerings: a yield accounting solution and an off-sites solution integrated with planning and scheduling systems. The company further announced that it has acquired
Spiral Software, a privately held company headquartered in Cambridge, UK. Spiral Software provides the only integrated
refining-industry solution designed from the ground up, bringing together feedstock data management, planning and scheduling. This means that Invensys Operations Management’s SimSci-Esscor solutions will now fully support and optimise the entire refining value chain, from crude trading to supply-chain distribution, including lifecycle modelling from design to start-up to performance optimisation - potentially saving customers millions of dollars every year (Fig. 1).
Optimising confectionary processes Operating from sites in the UK and USA, Baker Perkins is a leader in the supply of high-output machines and complete process lines to the worldwide confectionery industry. The company’s machines and services utilise the latest technology, to maximise efficiency and minimise cost of ownership. The company’s new generation ServoForm depositor is used for sugar confectionery such as hard and soft candies, lollipops, toffees, fondants, fudges and jellies. The servo technology used offers much greater flexibility and control leading to lower labour costs, reduced energy bills and faster payback. An Allen-Bradley CompactLogix programmable
automation controller (PAC) from Rockwell Automation controls all aspects of machine operation while an Allen- Bradley PanelView 1250+ touch screen HMI, mounted in the main control panel, helps operators to set up and monitor both the cooking and depositing processes from a single location. Initial process settings are stored as a recipe and are
downloaded to the machines, setting up the line at the touch of a button. The new ServoForm uses Allen-Bradley PowerFlex variable-speed drives combined with Allen- Bradley Kinetix servo drives to adjust and synchronise the various movements of the head, pistons and mould circuit for maximum precision and efficient continuous operation. As well as recipe control, the PAC and HMI provide full process visualisation, including real-time historical trending plus alarm management and history. ■
Model-based engineering reduces costs, increases throughput
approaches to reduce costs, increase throughput or quality and support capital decisions. Model-based engineering uses detailed predictive models of the process (or key elements of it) to identify significant improvements. These often do not involve capital expenditure: they may identify actions as simple as changing process operating temperature and pressure, or implementing a new seeding policy for a crystallisation process.
W In many cases the same model can be used
for many different investigations, or applied on a regular basis as market conditions change,
hen carrying plant optimisation projects, PSE uses its proprietary model-based engineering
generating multiple return on investment in modelling activities.
In terms of benefits, modelling can often identify ways to achieve the following without significant capital expenditure: reduce costs and improve quality – one customer’s polymer process batch time was reduced by 35 per cent; increase throughput or quality; reduce energy costs; reduce raw material costs; improve return on capital employed; extend catalyst life, reducing cost; and enhance compliance with environmental or safety requirements. PSE recently carried out a model-based engineering project on one of Samsung Petrochemicals’ purified terephthalic acid (PTA) plants in Korea.
The company has long experience with this product and used a set of high-fidelity process models and advanced methodologies for the detailed modelling and optimisation of the process itself. The two companies are expecting a reduction in paraxylene consumption that could save up to €1 million/y, a reduction of up to 15 per cent in acetic acid consumption – saving a similar amount, and allowing better optimisation of operating conditions – allowing more raw material flexibility.
Model-based engineering can also be used in the re-design of equipment for changing production, for example to establish optimal impeller design and nozzle placement. ■
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