Using Process Displays for Troubleshooting

using-process-displays-for-troubleshootingA lot of time and effort goes into the construction of the HMI screens and other display screens that are used to monitor and control production processes, so it is worth giving some time and thought to their layout and design. The most important consideration is how they can convey the most useful information in a timely manner to their intended audience.

This blog post deals designing process monitoring screens to better assist with troubleshooting efforts. It contains tips and guidelines on how to use PARCview’s graphics design tool, PARCgraphics, to address this goal.

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Process Data Compression: Why it’s a BAD Idea

data-compressionMost people are familiar with compressing data files so that they require less memory and they are easier to send electronically. Similar concepts are popular with process data historians. With process data, compression means reducing the number of data points that are stored, while trying to not affect the quality of the data. Compression can be accomplished using one of several algorithms (swinging door, Box Car Back Slope). Each algorithm uses some criteria to eliminate data between points where there is constant change (slope), within some tolerance.

The main drivers for compression are disk space, and network traffic or data retrieval speed. The goal of compression is to remove data that is “unimportant”. The proponents of compression make convincing arguments, like the shape of the graph is still the same. However, there are several drawbacks to compression.
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Process Control Loops: Trending PV, SP, OP and Mode

control-loop12Modern manufacturing and process industries are often largely run by distributed control systems (DCSs), with minimal input from operating personnel. This has largely been made possible by the evolution of computer and controller hardware and software.

The basic building block of a process control systems is the process control loop. Process control loops utilize sensors, transmitters, calculations or algorithms, processing systems, and actuators or outputs. Their ultimate goal is to help a process run in a stable, predictable, consistent manner. Some common examples of process variables that are controlled by control loops include tank levels, liquid flows, air temperatures, and steam pressures.

A large industrial processing facility, like an oil refinery or paper mill, utilizes thousands of process control loops. This type of facility also typically utilizes a data historian to store data related to their control system or systems, plus other significant data. This data contains a wealth of information that can be used as a powerful troubleshooting or optimization tool. The trick is knowing how to use it.
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Getting “High Performance” Process Data from your PIMS

high-performance-process-data-for-PIMSThe first step toward understanding and optimizing a manufacturing process is to collect and archive data about the process. Hopefully the system used to accomplish this is a “plant-wide” information system, or PIMS, which collects not just process data, but also quality information and laboratory results, and operations information such as upcoming orders and inventory. Collecting data and putting it in a historian is relatively easy, and most control system suppliers and some third party software vendors offer this capability. The real value of a PIMS is determined by how that collected data is organized, how it is retrieved, and what options are available to help you garner meaningful conclusions and results from the data.

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