Upstairs, Downstairs

Data Going Up, Data Going Down? Engineers and IT Shake Hands in the Middle as OPC Gives Way to XML, Web Services

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By Bob Sperber

About a decade ago, Kris Zywicki began studying ways to make Dow Corning’s information technology (IT) infrastructure as high-performance as the silicones it produces. Starting at the company’s hometown plant in Midland, Mich., he zeroed in on calculating the costs and risks of manual data entry on both sides of the production process, from enterprise resource planning (ERP) to the plant’s distributed control system (DCS).

By 2002, integrated data between the two platforms was saving the plant $650,000 a year. “Today,” Zywicki says, “just by doing automated data transfer, we’re looking at $4 million in cost avoidance.” And Zywicki, Dow Corning’s enterprise integration architect, continues standardizing and streamlining systems across more than 15 plants in the Americas, Europe and Asia.

So far, the company has implemented a single, global instance of SAP business software serving 9,000 users. Operational systems in various stages of implementation include laboratory, maintenance and historian/data-manager systems. Control platforms have been whittled from “just about every system you can name” to four.

Manufacturing and software standards are converging to produce a fundamental flattening of the DCS architecture. Today, instead of proprietary interfaces and custom programming, engineers and IT management can find common connections in standards that grew from Windows and the Web.

Today, penetrating a firewall is getting as easy as Web browsing. But before going Pavlovian at the prospect, and leaving the security issues inherent in this arrangement aside for the moment, engineers have to ask questions of such Zen-like simplicity, the answers aren’t always obvious.

  • What data do I need from the business system to run my process better? 
  • What data does the business need from me to run the plant better?

Data Down, Data Up

Most plants aren’t very integrated; reports circulating in the process industries indicate that fewer than 10% of plants have actually achieved a data path from the DCS up through the plant and into the ERP system.

Most orders and reports are still shared using email, phone calls, whiteboards and spreadsheets, “but we are seeing more and more requests from our DCS users to automatically receive schedules, says Dave Emerson, director of Yokogawa’s U.S. development center. Likewise, he says, production, compliance and quality reports coming up from the DCS should be automated at any reasonable cost. At the top of the ERP-to-plant data pipe, a single human error can foul up inventories and schedules for days or weeks, and be discovered only when when trailers and tankers pull up or away.

The data an ERP system sends down to the plant depends on the bill of material. At Dow Corning, data import/export varies with batch, semi-batch and continuous processes. In addition to tracing and tracing material inputs betweeen the DCS and SAP, production reporting up from the DCS is typically every four hours for, say, a week-long production run; batch reports are sent at the close of each batch.

“The whole business workflow is affected by these reports, so we can’t allow plants to under-produce or over produce or run out of raw material,” Zywicki says. Before his SAP-to-DCS integration project, he says “process schedulers would create process orders in SAP, then go back to the batch execution system and retype the whole production schedule—date, time, materials to be made, resources to be used... it was a lot of work, and mistakes happened.”

Typically the first data DCS users start integrating are final production outputs—number or barrels of oil filled, gallons of gas, liters of material. But getting to and making use of even this low-hanging fruit has its challenges. Integrator Dennis Brandl, president of BR&L Consulting, says, “the hardest thing is to figure out what that data actually means, to understand the production context.”

Single-value data transmissions are obsolete; today’s plants and businesses require much bigger data containers and manufacturing-specific software interfaces that can handle “full, complex pieces of information; we’re talking about whole histograms of data,” Brandl says. “That kind of integration requires you to build processes on your shop floor or into your DCS system to keep collecting data and making calculations on it. That’s when integration gets harder.”

Use the ‘App’ Map

Brandl’s into building processes; he’s chair of the ISA committee behind the ISA88 batch standard and editor of the ANSI/ISA95 family of control-to-enterprise integration standards. With roots in Ted Williams’ early-1980s’ Purdue Reference Model, “95” provides a model that end users, integrators and vendors can share in integrating applications at key layers in the enterprise. (For details on this model go to

Service-oriented architecture
Figure 1. Service-oriented architecture simplifies the links between “upstairs” and “downstairs.”

Only a fraction of production data need ever reach the business office in any direct fashion. “Only about 10% of management data is exchanged with operations management applications; and only about 10% of operations management data is exchanged with the business side,” says Dave Woll, consulting vice president with ARC Advisory Group. “Every step up represents less information by an order of magnitude.”

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