Promises, Promises, What's In It for Me?

Emerging standards and improved data connectivity hold the promise of helping manufacturers tie their plant and business processes into one neat package.

To many process engineers, packaging equipment can look like something from another planet. Often the controls part of a machine can be rudimentary in their view, and troubleshooting machines from many suppliers can be a headache to figure out. On the other hand, information technology (IT) engineers view both the equipment and control sides of the manufacturing equation as black boxes as they try to siphon out important real-time data to feed their business systems. The plant floor difficulties can lead to extended downtime as companies reduce staff, requiring engineers to assume responsibility for more production areas. The IT difficulties can cause lost profits due to increased inventory, delayed shipments or raw materials shortages.

But solutions to those dilemmas may be just around the corner. They hinge on the development of standard ways of defining machines, processes, programming, and data. The promise: easy data connectivity from process to packaging to enterprise, consistent operator interface and diagnosis methods, and, in the end, improved profits for manufacturers and their equipment suppliers.

Engineers involved in batch processing have developed—under the auspices of the Instrumentation, Systems and Automation Society (ISA)—a standard adopted by the American National Standards Institute (ANSI) known as ANSI/ISA S88. This standard identifies tag names and process “states” in a model that can be adopted by users and suppliers of batch automation processes. Another group developed ANSI/ISA S95, a standard that models data communications between the batch process and manufacturing execution system (MES) application software.

Usage migrates

Meanwhile, the OMAC Packaging Workgroup, part of the Open Modular Architecture Control Users Group (OMAC), has developed PackML, a subset of S88 for packaging that defines a state diagram for packaging machines and standard tag names for data.

Mike Lamping is a technology leader at Procter & Gamble, a Cincinnati consumer packaged goods manufacturer working with converting equipment. Lamping notes that many converting machinery manufacturers moved their designs from mechanical line shafts to electric servo control during the 1990s. “We have many things in common with modern packaging machinery. For instance, converting machines are also built in modules. The PackML model is not all that far from converting, probably just requiring some redefined states,” he adds.

Right now, there is very little communication in effect between converting and packaging, Lamping says. But it would be helpful to use the state model for converting. “When you are troubleshooting a machine, the model directs you to the right section of code,” he notes.

Even though bringing all the standards together in an enterprise-wide solution is very new, there are companies that are now reaping the benefits of implementing the strategy.

“We have been able to reduce our overall inventory value by up to 30 percent and achieve a flow of better and faster management information,” says Paul Bloemen, director of ICT, Brouwerij Martens, following the implementation of a three-phase business and production strategy at the Belgian-based brewers. Privately owned since 1758 and based in Bocholt, Belgium, Brouwerij Martens produces 10 basic beers within a portfolio of 200 finished products.

Wishes for projects

The brewery constructed an ambitious wish list for a new project. Among its goals were increasing business and production efficiency, reducing time to market, exposing product cost structures, enhanced management information, integrating the supply chain from vendors to customers, and standardizing technology that enables collaboration and traceability.

The first thing the company did was to install an enterprise resource planning (ERP) application in order to automate production planning, purchasing, manufacturing information, product costing, quality control and recipe management, along with sales and other financial information. For example, Martens bases its production schedule on sales forecasts eight weeks ahead. This information must be communicated in terms of raw material and packaging requirements. An automated Invensys Protean ERP system provides the relevant data in a form usable by each function, enabling the brewery to optimize stock levels, capacity and manpower.

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