Oracle is the tip of an intelligent iceberg

Bromford Iron and Steel, the hot rolled steel manufacturing part of Hill and Smith Holdings, based in the West Midlands, reports "significant" energy cost reductions (10—15%), as well as improvements in production costing, scheduling, management and control, following implementation of an unusual business intelligence cum plant production analysis tool. Like many others in the steel industry, Bromford is a very high energy user. The firm makes a wide range of steel types and long sections to order for a spread of industrial clients, and runs large, high temperature furnaces and substantial hot rolling mills (21 stands) driven by big electric motors. There’s also a huge compressed air plant (600cfm delivery) to drive the electro-pneumatic automated controls and the rest. Bromford was operating all this based on received wisdom and best practice handed down over decades of steel rolling craftsmanship. But with the coming of the Climate Control Levy and ever tougher economic conditions forcing a drive towards greater efficiencies, the Bromford management team needed to do rather better. However, while it was aware of differences in energy used per tonne – in some cases factors of 20 even on similar products – and steel wastage across its product range, the firm needed detailed real time historical information correlating products, processes, production parameters and events to move it forward. A whole new way So two years ago Bill Venables, Bromford’s chief engineer, brought in ICEberg, a production analysis tool from developer and system integrator IEA, now BsquareT, founded on Oracle Express OLAP (on-line analytical processing) and Oracle 9i database technology from the firm’s Business Intelligence Division. And within a few weeks of installing the system, the team was discovering some causes – and their solutions. Venables explains that there are several production variables. "Steel comes out of the furnaces at 1,140 to 1,200C, and on to the rolling mill. We make various sections, from stubby and thick to thin, so speeds across the rolling mill are very different. Thicker sections go down in one and a half minutes, but smaller sections can take 15 times as long, and it’s losing heat all the way – we’re cascading canal water to lubricate the mills and wash off scale all the way. "But to get the material performance, the rolled steel still needs to be at 800C when it reaches the final stand. So we have to heat steel billets for thin sections to a higher temperature than thick sections." Sounds simple, but with other variables in terms of roll speeds and diameters to suit the individual products there are choices. Furnaces have individually controlled multiple burners (at the rear and side) and Venables admits that before they might have fired all burners for a thinner section, "but we wouldn’t know if we’d gained anything or thrown energy away up the chimney." Changeovers and choices And there are other issues. Says Venables: "The thinner sections are likely to have more problems during production – like cobbling in the rolling mill." And some steel changeovers need more setting up time. But the plant is running all the time so it all increases the total energy consumed for that tonnage. Bromford spent £26,000 on ICEberg for beta testing, and Venables says it was continuously modified and developed until three months ago – although he insists it started producing results almost straight away. In operation, the system samples real time data from the mill every minute – generating 1.5Gbytes a week. Says Venables: "It counts the billets out of the furnace on a time basis. We monitor the temperature of the furnace zones, the billet temperature outside on the rolling mill, amperage of the motors on the main roughing mill and progress of the billets at certain stands and at the final shears. We know if there’s a problem and the reason for it, and the system ties the operation of the mill to the sizes going through." He says that with this detailed historical data and ICEberg’s drill-down facilities, the firm has been able, over time, to isolate product runs, types and sequences that caused the greatest energy variances, and to identify key production parameters. As a result, it has been able to establish more efficient and profitable processes and schedules – and a lot more. For example, it allowed the team to look at energy losses during changeover times and breakdown times for each kind of product, and develop minimum run lengths and costs. It also allowed them to identify which product would be the most energy and cost efficient to switch to for virtually every changeover. BsquareT’s Steve Hudd explains ICEberg as an "occupacity" aid: "It’s about monitoring rate, yield, plant utilisation – similar to OEE (overall equipment efficiency) in discrete manufacturing – and people and raw materials, as well as what happened relative to the products they’re producing. The system can report by time, date, product, downtime, yield, utilisation, machine settings. It gives reasons for each stoppage. In fact it provides a direct portal to exactly what’s happening in the plant. It’s a production man’s dream.” Venables now uses this plant intelligence to influence everything from Bromford’s weekly production meetings – helping to determine quotes, best production sequences and the like – to plant maintenance decisions. "We use the system to help us decide whether to take a job or not. For example, spring steel is difficult to make and [customers] usually only want two tonnes – we might have to use three or four to get the quality. But if we have an order for a similar product we might be able to sequence it in economically." And he adds: "We can see which parts of the plant aren’t performing well and correlate those against production problems and stoppages. So we can see if something worth just £300 might be costing us thousands in lost production." And the team has also found some very simple changes that generated huge savings. Venables: "We’ve saved about nine hours of furnace usage a week. We thought we needed four hours to run it up to temperature, but with ICEberg we found we could start it two hours later – and that’s on a 17 tonne per hour, 450kW per tonne furnace.” For the future, he says,"We want to link it to our compressors and air usage. We’ll use it to see, for example, whether the fitters on the night shift switched them on for hours but only used it once..." Bromford now has a much clearer understanding of where energy is being used. Venables concludes: "From the period we installed ICEberg, we have seen a reduction during up-time working from 117 kilowatt-hours per tonne to 95."