3 Ways to Use Information Modeling for Continual Improvement in Your Enterprise

improvement

The concept of continual improvement has been a regular feature of modern manufacturing enterprises. Its gaining favor now in different circles, and for good reason. Continually making small incremental improvements to business processes has proven time and again to have a positive impact on production quality, efficiency, and safety. What’s not as well known, however, is how much more effective continual improvement programs can be when used in conjunction with an information model.

An information model can be thought of essentially as a virtual representation of your enterprise, and it provides the organizational and relational structure of your enterprise’s data. Providing context and organization to the raw data is the first step in turning it into actionable information.

Data included in your information model can be drawn from nearly any source. Include data from databases, web services, sensors, PLCs , calculations, real-time user input, or data from other enterprise applications like ERP or MES systems – essentially anything of relevance that can add value and support decision-making.

By modeling your information in this way and providing context to your real-time data, you can visualize your asset management data alongside your process control data, or your maintenance data alongside procurement data. Any data relevant to your business processes is now accessible to your visualization system, and opportunities for optimization become much more apparent when data is presented in context.

For instance, you can visualize how a particular motor’s production throughput is affected by changes in the Overall Equipment Effectiveness (OEE). You can see how the OEE is affected by maintenance operations. The sort of real-time situational awareness enabled by information modeling reveals new opportunities to lower maintenance and operation costs by maximizing asset performance. By defining the relationships in your information model, the data that you visualize becomes much more understandable and actionable.

Another – and perhaps greater – benefit of information modeling is the ability to track the results of incremental changes in real-time across multiple channels.  This allows for faster analysis and greater collaboration. It also becomes much easier to establish new standards, as information entered into your information model is immediately accessible to all who use it. Also, additional media – like videos and manuals – can be included in your model to ensure that all personnel have immediate access to the latest standards and best practices.

There are many ways information modeling can help your continual improvement efforts. Here are three categories of benefits many business owners are already seeing.

1.      Analytics, Reporting, and Condition-Based Task Automation

If managed through the right software system, one of the great benefits of information modeling is that your data is normalized and available in a consistent format, regardless of where the raw data was generated. This presents tremendous opportunities for data analysis, reporting, and task automation. It allows machine-to-machine communication, business-to-machine communication, and business-to business communication. An event in one device or location can automatically trigger an action in another device or location. Automated reports can include data from multiple sources. This is the essence of the Internet of Things (IoT) – the interconnection of all of assets and their associated data.

This also presents opportunities for improvement maintenance operations, as machines can generate their own work requests or alert personnel of potential problems. The possibilities are truly endless when we free ourselves from the data silos many of us struggle to integrate daily.

2.      Data Mining and Activity-Based Intelligence

The US Department of Defense employs a process known as Activity-Based Intelligence (ABI) to find useful details in large sets of data. The process involves creating an automated mechanism to sift through large sets of data in search of anomalies.

Today’s industrial enterprises are finding ways to employ similar techniques. Huge amounts of data are being recorded and opportunities for improvement are known to exist, but how do we know what to look for and how do we find it? The same sort of ABI employed by the DoD is finding a place in the commercial world.

If we can review our historical process data to define the circumstances surrounding certain conditions (unplanned downtime, spikes in energy consumption, etc.), we may be able to recognize repeated patterns or anomalous activity related to these specific circumstances, thereby enabling us to act to correct the situation before it happens again. By finding the data that stands out from the rest, detailing the characteristics of that data, and looking for those characteristics elsewhere, we may be able to pinpoint causal relationships that were previously obscure or misleading.

On the flipside, the same techniques can be employed to define the circumstances surrounding periods of extended productivity or energy efficiency. The same techniques used to discern the cause of deficiencies can be used to optimize asset performance and improve the quality and efficiency of our processes.

By creating analytic mechanisms aligned with the principles of ABI, we are able to create a safer, more efficient, more productive work environment.

3.      Repeatable and Scalable

As you make the changes that will lead to a more efficient, more productive, and safer business, these changes become part of your information model.

Your information model not only helps you identify opportunities for improvement and publicize updated standards and procedures, but also gives you a means for endless repetition and growth. Your information model is progressive; it can always be modified or expanded. As you make successful optimizations, any changes made to your information model can be easily repeated for any other relevant processes. You are also able to expand your model by adding new locations, new assets, new process cells – whatever it is that you have optimized about your model can be repeated or extended indefinitely.

Excerpted from the whitepaper “Continual Improvement with Status”, downloaded at www.scada.com.

Kaizen and the Philosophy of Continual Improvement

kaizen

One of the mostly well-known and widely used philosophies of continual improvement originated in Japan. It is known by the name, kaizen, which translates approximately to “good change”. Kaizen has been employed in a wide range of industries – healthcare, banking, psychotherapy, government, and many others. In business, kaizen typically refers to activities that continually improve all business functions and involve all employees.

Kaizen is frequently used to optimize purchasing, logistics, and supply chain processes, and has been employed in lean manufacturing processes to help eliminate waste. Kaizen was first used by Japanese businesses following World War II, and has since spread throughout the world and been implemented in environments outside of business and productivity.

Kaizen places a strong emphasis on employee feedback, encouraging employees at every level to apply the scientific method in learning how to spot and eliminate waste in business processes. Kaizen can be applied in a very small, personalized way, or it can apply to larger processes that involve groups of employees. In a very general way, the Kaizen methodology can be understood as:

  1. Discovering opportunities for small adjustments based on process data and customer feedback
  2. Implementing these small changes incrementally
  3. Monitoring the results of each individual adjustment for a certain period of time
  4. Using the new data to make adjustments
  5. Defining the results of successful adjustments as standards, and using these standards as baselines for additional improvements
  6. Repeating this cycle indefinitely

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The kaizen philosophy aims to improve process efficiency, quality, and safety by making it easier for employees to do their jobs well and with confidence – rather than expecting them to work harder through incentives or fear of replacement.

Improvements made using the kaizen philosophy are typically on a much smaller scale than those found in the “command and control” improvement programs popularized in the mid-twentieth century.

This system of incrementally improving operations is also known the Shewhart Cycle, Deming Cycle, or PDCA (Plan-Do-Check-Act).

Similar ideas are investigated in the realms of Organizational Development (OD) or Business Process Improvement (BPI). The general intent of all of these philosophies is the same: to maximize the value of all available material, personal, and intellectual assets and to improve business processes by making use of resources that are already available.

Like the methods outlined above, other popular methods like Six Sigma, Lean, and Total Quality Management emphasize employee involvement and collaboration, standardizing processes, and reducing variations, defects and cycle times.

Excerpted from the whitepaper “Continual Improvement with Status”, downloaded at www.scada.com.