With more than 500 projects completed with less than one year to payback, Cargill Optimizing Services understands how to decrease costs and increase yields in the food and beverage industry.
This case study illustrates the value in looking at a production site holistically. There is much to be found when looking beyond the usual suspects such as the utilities area and the production lines.
CIP opportunities are sometimes overlooked because they touch safety and quality, are not immediate concerns during production and involve complex controls. However, CIP systems can consume significant quantities of energy, water and chemicals, and can impact plant availability. With energy as a foremost concern, and water as an emerging sustainability issue all across the globe, we recognize that CIP systems offer significant opportunity – and in fact our experiences suggest that a focused analysis can reduce cost, energy use and water use by over 40%, and cycle times by over 10%.
- Asset Utilization
Clean In Place (CIP) systems present an oft-overlooked area of opportunity in many food processing facilities, particularly those with short production runs and/or many different products. Many process improvement efforts ignore CIP systems because they fall outside the production envelope and involve complicated control logic. Recent Cargill Optimizing Services experience suggests that review of CIP systems can reduce cycle cost, energy use, and water use by over 40%, and cycle times by over 10%. CIP systems vary widely, but a “deluxe” system includes four tanks (cold and hot water, caustic, and sanitizer). The tanks’ contents or outlets are steam heated, and piping / valves allow switching between sources and destinations. A generic system schematic appears in Figure 1.
Preliminary efforts focused on energy and water reduction, and the structured modelling approach quickly made it apparent that 40% energy and cost savings can be achieved through relatively minor changes to recycle strategy and equipment. A focused engineering team iterating with the plant equipment should be able to achieve similar results, albeit with a lot more work hours invested.
Reducing the cycle time, particularly while maintaining the energy and cost savings, requires more complex operating changes. This is where the power of a rigorous model became particularly apparent. Early iterations cut cycle times by over 10% and reduced water use by over 40%, but energy and cost reductions were “only” 20% and 30%, respectively. The model results, however, show where in the cycle energy is consumed and rejected. This knowledge was used in further iterations recaptured most of this opportunity by modifying the sequence of the steps. The final iteration reduced cost, energy and water use by over 40% as compared to the base case, and the cycle time by 12%.
An important caveat to these findings is that CIP is critical for food safety and quality in most plants. While a
model can estimate the operational savings, recommendations need close scrutiny from the full operations
team before implementation. A second caveat is that a very broad range of CIP approaches and equipment is in use, and the potential will depend greatly on prevailing local conditions.
This case study illustrates, though, how a model can iterate through many potential options and get “clean” data to compare their performance against multiple criteria. In this case, plant trials would have been lengthy and created potential food safety or quality concerns. Success against one or two of the performance indicators could probably be achieved by a focused engineering team, but improving all the measures would be much harder
without the model.
While there are clearly opportunities in considering CIP in isolation, there is typically even more potential in modelling the full site. Our CIP model can integrate into a holistic site model. Capturing the rest of the plant’s operation can identify additional opportunities like sharing waste heat to reduce CIP energy costs or recovery of water streams to reduce fresh water use.
When to consider
This study is most applicable to plants processing multiple batches or SKU’s through common equipment. It is particularly relevant if more than 5 CIP cycles are run per day and if the CIP protocol has not been investigated for some time.
About the author
Charles Sanderson is the Technical Director of Cargill Optimizing Services, based in Minnesota, USA. He has led the development of Cargill's simulation capabilities for over ten years. He and the team have deployed the tools in projects across Europe, Asia and the Americas. Charles graduated in Chemical Engineering from Imperial College, London and received his PhD from Sydney University in Australia.