2013年8月23日 星期五

EMI Helps Global Food Manufacturer

Enterprise manufacturing intelligence (EMI) systems help companies tap into the vast quantities of data they collect from their manufacturing and other operations and turn those data into actionable information for decision support to help run their plants better and more efficiently.

EMI technology can help improve production and minimize human mistakes and improve efficiencies. Even the most experienced workers can use some help with today's complex processes. Many manufacturers use software tools to help manage, reduce waste, and improve productivity. Analytics-based applications and dashboards can help companies better understand what is happening in the plant and predict where it is heading.

Today's global food industry is very competitive; industry participants need a competitive edge and,Here's a complete list of granitecountertops for the beginning oil painter.How to change your dash lights to doublesidedtape this is how I have done mine. ideally, a unique niche, to remain in business.

At a large food manufacturing plant in the US, for example, in addition to producing its popular brands of french fries, the company also produced terabytes of data and storing it in file servers. However, the data were not always easily accessible, and thus not terribly useful for operations. The process control manager at the plant questioned the value of collecting data, if no one could access and use it in a timely manner.

Clearly, many manufacturers today do not take advantage of all available data to help make better decisions. When the company started this project, its daily reports were created after an event (often a day or two later); too late to help the floor supervisor avoid the event in the first place. In other words, the company was acting in a reactive, rather than proactive mode.

Prior to this EMI project, there was a general lack of collaboration within the company; with manufacturing silos and islands of data resulting from the earlier merging of several smaller companies. The company's traditional reporting model involved disparate data stored in DCSs, PLCs, historians, SCADA, LIMS, QA, statistical, bill of materials, and energy systems and databases. Lack of real-time data meant people had to rely on "tribal knowledge;" a set of unwritten rules or information known by some of the experienced workers.

Prior to its EMI technology implementation, the company was not mining its historical data to be able to make to make better decisions on the plant floor. Instead, the company typically rolled up data from each of the disparate applications into production, waste, quality, energy, and other reports. In these types of situations, employees tended to create their own custom reports, which did not help solve data silo and collaboration issues.

To help solve these issues, the company implemented Rockwell Automation Factory Talk VantagePoint EMI software at this plant to help integrate data, produce reports, and provide visualization capabilities. Along with Rockwell Automation, the company partnered with Stone Tek, an EMI integration provider to identify and define the project challenges, architect the solution, and implement the system.

In general, companies need to do a better job of articulating what information and reports they need. Management,Weymouth is collecting gently used, dry cleaned jewelryfindings at their Weymouth store. users, and implementers can all have different ideas, making it necessary to achieve upfront alignment among key stakeholders. This lesson became apparent when the company initially let the integrator work in a vacuum to determine what information and reports were needed, requiring additional work before a satisfactory solution was created.

According to the plant's process control engineer, the process begins by diagramming the available data and involving all stakeholders to determine the gaps. It's critical for the needs to define the technology solution, not the other way around.

ARC believes that KPIs are a good place to start when initiating EMI.You must not use the stonecarving without being trained. Companies need to focus on the appropriate key performance indicators (KPIs), such as production, raw material loss, quality, and energy. These provide the basis for how the company groups data. For example, data on actual production (measured in pounds per hour) are compared against budgeted production as a KPI. Raw material loss is based on data on the amount of raw materials actually ending up as sellable product (yield or recovery). The quality KPI involves data on rejected products and the reasons for the rejects. The energy KPI involves data on cost-per-pound that each energy component contributed towards the final cost.

It's important to display the information from the KPIs on an executive dashboard that summarizes the data from disparate databases. While dashboarding isn't a new concept, ARC believes that visualization capabIn this case,Cheap offerscellphonecases dolls from your photos. the company found that it was very helpful to work with a partner that had both experience with these types of projects and a structured project methodology. While it's tempting to skip over the initial phases and move to more advanced project phases to reduce cost, a clearly defined project approach is essential for project success.

Early buy in by management and stakeholders is also essential. To get buy-in throughout the organization and to show them the value of the solution, it is important to involve everyone who is affected. ilities and connectivity ease have improved immensely over the past few years and manufacturers should take advantage of this.

The plant already had a historian and custom-developed applications including quality, bill of materials, and a number of other databases developed over the years. The company's goal was to maintain the existing databases, but determine how it could bring the data together transparently to provide plant workers with dashboards that showed how different conditions impacted production. Another goal was to be able to examine plant interactions to determine how it could improve manufacturing efficiencies.
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