Copyright DSL UOW 2010

Process Improvement and Energy Efficiency with Supply Chain Optimisation Audit (SCOA) Do you find: Localised improvements not aligned to globalised plant objectives. Operations Managers unable to identify and commit to even 2% sustained improvement in productivity, yield or energy efficiency. Cost of all forms of energy and conversion cost is rising steadily. Conversion costs rise significantly whenever capacity utilisation deviates from the sweet spot. Data overload with large amount of contaminated data hiding the valuable information about efficiency. Is any or ALL of the above applicable to you? If the answer is yes & you don’t like it then you should contact DSL for a SCOA investigation…

The SCOA Challenge At the Decision Systems Lab believe what we preach. We apply SCOA to solve real world problems If your supply chain : moves material in million tonnes transforms and routes energy over 100MW Provides services to a 0.2 million people or more Uses multiple forms of energy worth each tariff being in 10s of million dollars is exceeding capacity limits and needs a major upgrade estimated to cost over $10 million Has large periods of under utilised capacity We offer the SCOA challenge to save you a million dollars or more per annum. Contact us as you have a lot to gain. Our experts are always looking for a small number of ongoing projects to apply SCOA as a continuing demonstration of the methodology. Read more how it works....

No Gain No Reward.... The DSL SCOA team takes on a project and develops appropriate process measures based on data and benchmarks historical performance. The DSL SCOA team sets a target in consultation with you and defines the improvement target, the measurement method and the formula for reward to SCOA team for achieving target. The SCOA team works with you at actual costs for a period of 6 to 12 months until the target is achieved. The SCOA team presents the results and claims its formula based reward for achievement. The SCOA team maintains an annual audit interaction to validate the improvements are being sustained. How the SCOA Challenge works

Independent review of your high value and or high loss supply chains by proven SCOA experts to identify opportunities. Development of new incisive productivity, resource use efficiency and yield measures about your key supply chains from existing data. Implementation of lean improvements which lead to sustainable annual multi million dollar savings. Discover early, any departures from the plant best practice. Rectify such aberrations early, preventing unnecessary loss and maintain close to best practice performance. Discover better alternatives in adjusting for unit level major shutdowns and other events by globalised planning and scheduling for improved results. Reward the SCOA team only if they deliver results as per previously agreed criteria and targets. Benefit to your organisation

The answer is any organisation that has one or more supply chains of a billion dollars or more. The supply chains may carry value in any form including:  Raw materials  Intermediate products  By-products and finished goods  Energy generation, storage, distribution  Soft services like communication and Information,data, ICT based entertainment.  Hard services like transport, electricity, water  Industry could be Steel, Aluminium making and transforming, Mining coal, iron ore, gold, tollways, railways,defence, shipping, ports and warehousing, voice and image communications, broadband networks, utilities, Airlines, Catchment Authorities, Tourism boards... So who should take up the SCOA Challenge?

Contact Head Sustainability and Logistics practice Saugato MukerjiSaugato Mukerji mobile skype shaunak100

Project Story The following iconic story is a simple yet powerful illustration of two important pillars of the SCOA methodology, namely : investigate repeatable patterns of variability in major supply chains Reduction in variability of key supply chain parameters in most cases gives savings in service cost, energy, material or frees capacity for productive use. In a certain steel plant the there were several coke oven batteries. The vintages and designs of the batteries were not identical as they had been commissioned at different points in time either as replacements for batteries being decommissioned or for capacity expansion. The coke ovens were fired by a mixture of blast furnace gas(BFG) and the coke oven gas(COG) produced as a by product in the blast furnace and coke oven batteries respectively. This consumed 6 to 10% of the COG make and the rest of the COG was used as a fuel gas in other parts of the integrated steel plant. Looking at the pattern of the variation we noticed there was an unmistakable consistent sine wave with a time period of 60minutes in the pattern of variation of COG fired in the batteries. Mathematically the pattern looked like V = V1 + V2Sin Ɵ There seemed to be no real explanation for this consistent pattern of variation.

Project Story continued... SCOA recommends investigate the domain and details of the supply chain to find causes of variation. In this case it emerged the different ends of the oven were called inners and outers. The inners and outers were fired alternately at an interval of 30 minutes. Further that two of the batteries fired the inners at a rate different to the outers to compensate for some oven design issues. Armed with this new information the combined COG consumption was decomposed and individual battery consumptions were studied. As expected two of the 4 batteries showed a clear square wave pattern of COG consumption. Looking closer it was noticed the square waves had a periodicity of 60 minutes and further that the two square waves has a relative displacement of 5minutes. Suddenly it was very clear why the combined consumption pattern showed a sine wave shape. In maths when you superimpose two square waves you get a sine wave. The SCOA questions now were could the sine wave pattern in the COG consumption be eliminated ? was there going to be any saving by eliminating the variation? Both answers were YES. The explanation is in the next slide

Project Story continued... The variation was easy to suppress by aligning the firing pattern of inners and outers of the two batteries, such that the inner ( hi firing) of one coincided with the outer(low firing) of the other and vice versa. The graphs below show the before and after and confirm the sine wave variation was suppressed successfully. Steel plants normally have cogeneration to use the excess fuel. In this plant the boilers did not have the capability to vary the steam generation on a continuous basis. As a result conservative settings were maintained often for several hours. Boilers had 8 burners and the fuel could be controlled by switching individual burners on or off. The fuel rate was set at a level that would ensure there were no shortages even at the peak of the sine variation in the battery COG consumption. Conversely this meant additional fuel was not utilised at the bottom of the sine wave pattern. The excess fuel is normally flared as it is too voluminous to collect for long periods. The density is around 0.4kg/m3 so 100,000m3 tank will only hold 40 t. Before After

Reserved for battery operations Additional 2000m3/hr COG released for generation / stabilising COG system pressure 19 Potential Flare BEFORE AFTER 16 Variability reduced from 6000m3/hr to 2000m3/hr 60min km3/hr 60min

Project Story continued... Did eliminating the sinusoidal variation give benefits? There is a generic increased stability benefit from reducing supply chain variation There could be site specific benefit for a percentage of the time from reduced waste of COG. In this example the Co-generation capability was not excessive, and on many occasions was further reduced by equipment outages. This meant the additional steady 2000m3/hr of COG made available for cogeneration use, was only utilised for part of the time. Looking at historical data and making a conservative assumption that the 2000M3/hr of COG could be used only 40% of the time the annual benefit works out to $0.77m p.a. ( calculations are in the next slide) Benefits from reducing sinusoidal variability. There was an immediate elimination of patterns of instability in operation of down stream reheat furnaces which consumed COG. The sinusoidal variation tended to aggravate the pressure drops in the COG main during fuel shortage events. This typically used to occur when the high consumption events of consuming plant lined up with the high part of the sine wave. While the shortage events still continued to occur their intensity reduced. The benefits of stability are large as will be confirmed by 6 sigma practitioners. Some time after this change the cobble rate of the hot strip mill fell by 1% while the circumstantial evidence points to the improved stability it is almost impossible to make operations accept it.

Annual Benefit calculation Natural Gas energy cost4$/GJ Power tarif66$/MWH generation efficiency25% CV of COG21MJ/m3 hourly rate of saved COG2000m3/hr hourly rate of energy saved content in COG42000MJ/hr hourly rate of energy converted to electricity10500MJ/hr 1MWH3600MJ/hr Hourly additional generated electricity2.9MWH Fraction of year when genration capactity not already saturated at 100% 0.4 Annual additional power generated10220MWH Annual value of additional power$674,520$ Hours when energy is short and NG is in use600hrs savings costed at Natural Gas energy cost$100,800$ Total saving$775,320 Thank you Copyright DSL UOW 2010