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Reducing Material Costs by up to 30%
技术
- 分析与建模 - 预测分析
- 功能应用 - 制造执行系统 (MES)
适用行业
- 食品与饮料
适用功能
- 流程制造
- 质量保证
用例
- 机器状态监测
- 预测性维护
- 过程控制与优化
服务
- 软件设计与工程服务
- 系统集成
挑战
Customer satisfaction is a critical issue for the McCormick Flavor Division, which produces sauces, dressings, and condiments for major restaurants and fast food chains. The company faced challenges in presenting data during customer audits and needed to improve their process control to reduce waste and improve the bottom line. They also needed to better understand the natural variation in their processes to make adjustments closer to target fill weights and reduce material costs.
关于客户
McCormick & Company, Inc. is a global leader in flavor, producing a wide range of products including sauces, dressings, and condiments for some of the world's largest restaurants and fast food chains. The McCormick Flavor Division, located in South Bend, Indiana, is dedicated to maintaining high customer satisfaction and continuously improving their processes. The company has a strong focus on quality and efficiency, leveraging advanced data acquisition and analysis tools to optimize their operations and meet stringent customer requirements.
解决方案
McCormick implemented Hertzler's GainSeeker Suite to enhance their data acquisition and process control capabilities. By using control charts within the GainSeeker Suite, the company was able to listen to the 'voice of the process' and understand natural variations. This allowed them to adjust processes closer to target fill weights and reduce material costs. The automated data collection capabilities of GainSeeker significantly reduced the cost of obtaining data, enabling the company to perform more frequent and targeted checks. This system also allowed McCormick to better understand the operating range of their equipment and reset specifications to reflect actual process capabilities. The company plans to expand the use of GainSeeker to include temperature monitoring for coolers, ensuring tight temperature control and automatic notifications for special cause variations.
运营影响
数量效益
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