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Basic Knowledge Understanding Data: MES in Digitalization

Editor: MA Alexander Stark

The mere digitalization of existing systems rarely achieves the expected outcomes. Manufacturing companies must first gain a clear understanding of their processes and operations. The MES experts from Critical Manufacturing show how to get there in five steps.

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If you want to digitize your company successfully, you first need to understand its processes and value chains. Otherwise, data remains just that and does not turn into information.
If you want to digitize your company successfully, you first need to understand its processes and value chains. Otherwise, data remains just that and does not turn into information.
(Source: Critical Manufacturing)

The English poet Alexander Pope once said: “A little knowledge is a dangerous thing." In connection with Industry 4.0 this statement is absolutely right because entrepreneurs sometimes get carried away with making decisions without fully understanding the real needs of their organizations and supply chains.

It is common understanding that technological breakthroughs such as the Internet of Things (IoT), Augmented Reality or Big Data analytics will play a major role in the Industry 4.0 environment. However, access to these technologies does not make a company and its production an “Industry 4.0 company”. IoT provides a lot of data that, without a meaningful integration of the relevant IT applications, will stay exactly what it is: a lot of hard to understand data.

Technology-Driven Approaches May Be Misleading

If the data analysis only comprises applications on the lowest level and only in relation to machine data, without considering relevant feedback and information from the other parts of the value chain, then all figures and the supposed knowledge generated from them will not deliver the result demanded by the corporate strategy. A lot of knowledge - or rather believing to know a lot - can therefore be a dangerous thing.

Top managers should therefore resist the impulse to get started straight away and only implement a single piece of the industry 4.0 puzzle. Rather, they should understand what needs to be done and seek the help of experienced experts.

It is not unusual for process managers and top managers to be infatuated with new technology. The roadmap we present in the following is designed to help companies maximize the value of introducing digital innovation into their value chains by first understanding their own manufacturing process, then aligning their business process accordingly, followed by monitoring and improvement processes.

Step 1: Visualization of Technical Processes

It is important that all technical equipment that is part of the manufacturing process is visualized and described. With the emergence of IOT, it is possible for almost any processing plant (large or small, new or retrofit) to communicate using intelligent sensors, RFID or WIFI-enabled equipment. Other machine controls are equipped with PLC or OPC and thus have the ability to communicate their own status or possible problems. Systems with exclusively manual input, which are nevertheless part of the process, should also be visualized. Only then a clear image of the current production process can be created.

The use of a MES (Manufacturing Execution System) plays an important role in creating a clear visualization of the existing process. The MES acts as a virtual link for all process plants or machines and enables the process flow to be documented, analyzed and improved. Any part of the plant that is IOT ready can be linked to the MES application, which serves as a unified platform for all information collected from these plants. This applies to systems with PLC and even to those without electronic communication capability.

Step 2: Assigning Business Processes

After the breakdown of the production process and the determination of the function of all technical equipment, the next step is to visualize the business process. This step is the key to an integrated value chain, which will profit from Industry 4.0. A clear and comprehensive understanding of how the functions relate internally to manufacturing and how the entire manufacturing function connects with other parts of the value chain, such as suppliers and customers, is essential to facilitate the digital transformation of the entire value chain (not just of the shop floor).

At this stage of our plan, it is necessary to connect all functional areas of a company with manufacturing and to analyze their correlations. We need to understand how research and development is linked to manufacturing and how information is exchanged between these two organizational units. Similarly, all aspects of business operations must be connected with the core manufacturing area to understand how the internal process as a whole integrates with other actors in the value chain.

At this point, it is crucial to take interfaces between different IT applications into account. For example, if the LIMS application used in R&D (LIMS = Laboratory Information and Management System) cannot establish a connection with the MES used for production management, this results in ineffectiveness. Then, integration and cooperation are limited For, an industry 4.0-ready value chain, the end-to-end connection of all elements that make up this value chain is absolutely essential. CRM ERP MES & SCM MES PLM integration is the most important consideration in this context.

Step 3: Gain Visibility in Real Time

Once the manufacturing process has been visualized, the next step is to monitor it. KPI data, engineering data, reports and all types of online analysis should be generated and analyzed in order to provide clear real-time visibility of the current manufacturing process.

It must be clear that - depending on the IT application used - the quality of the information generated for successful monitoring of the process can vary from good to poor to completely unreliable. Consequently, it is "decisive for the battle" to have an MES-expert at hand to ensure that all process-related information is captured in real time and the data is forwarded to the right people in the value chain.

Real-time SPC (Statistical Process Control) capabilities of the MES, combined with the ability to extract data not only from process plants but also from ERP, CRM and SCM applications, are essential for a successful and holistic monitoring process. At this monitoring level, it is revealed how the current production process and throughput is carried out and where issues and shortcomings arise. This stage of monitoring is extremely important because it prepares the ground for the introduction of other industry 4.0 relevant technologies. In addition, it enables process owners and partners along the value chain to measure current data and understand exactly where in the value chain the opportunities for improvement exist.

Step 4: Optimization of Manufacturing Processes

Once the status quo is clearly understood, the process of developing digital manufacturing can be moved forward to the next stage: Process optimization, i.e. the improvement of problem areas identified by monitoring. In this phase, incremental changes are made to the production process in order to improve the process results and thus the added value.

A transformation in production planning towards orchestrated detailed planning and fine-tuning of processes, introduction of yield management and associated cost savings as well as preventive maintenance are to be realized in this step. Of course, the MES-Application plays a key role in achieving the efficiency and effectiveness goals.

Step 5: Make Operational Processes "Smart”

The next step in the roadmap leads us to the point where Industry 4.0 really comes to the fore. A complete virtual image of the production is the basis for virtual reality scenarios over the entire production process. Improvement at this level has the potential to completely change the current production flow and planning.

This step can be very disruptive or destructive, but in turn offers the potential for quantum leaps in process improvement and material flow planning. In this phase, all physical components of the process exist as virtual instances, including their connections to the various functions inside and outside the organization. This enables significant improvements because those responsible can now start viewing the entire process through integrated applications and a continuous data flow.

This can lead to decisions such as the relocation of a machine group, the use of a specific loading shaft for material loading, or the addition of a finishing step in the distribution warehouses. Such decisions would never be possible without a comprehensive understanding of the entire manufacturing process of all the physical components involved and of the production process.

Looking back on the five phases of the digital manufacturing roadmap, this sequence of measures offers the best opportunities to take full advantage of industry 4.0. The importance of IT applications such as MES throughout the entire process needs to be emphasized once again.

The final step on the road to a powerful smart manufacturing vision allows industry 4.0 functionalities to be exploited. The newly created cyber-physical environment enables the use of virtual reality scenarios. Process owners can view the manufacturing process from start to finish in real time and make dynamic changes using MES to improve performance and achieve the required process objectives.

The final step on the road to a powerful smart manufacturing vision allows industry 4.0 functionalities to be exploited. Process owners can view the manufacturing process from start to finish in real time and make dynamic changes using MES to improve performance and achieve the required process objectives.
The final step on the road to a powerful smart manufacturing vision allows industry 4.0 functionalities to be exploited. Process owners can view the manufacturing process from start to finish in real time and make dynamic changes using MES to improve performance and achieve the required process objectives.
(Source: Critical Manufacturing)

Once the digital twin of the manufacturing plant is created and the MES application integrates IOT, the next step in the digital manufacturing roadmap would be the use of augmented reality scenarios, using mobile devices or VR-activated glasses or similar digital devices. Process owners are then able to obtain the exact status of machines, raw materials, orders, schedules and problems by simply pointing their mobile device at a piece of equipment or pallet of material.

Imagine how in the future workers plan process operations or pass-by maintenance, how they analyze the machine status with their VR glasses and identify and correct problems before they can affect the subsequent process. The possibilities for process optimization are unlimited. But the key is to follow the roadmap logically to reach the stage of "digital nirvana". But wait and see, it gets even better:

Offline Analysis Enables Better Decisions

While online analysis and the use of SPC-like applications enable process optimizations and deviation protocols, offline analysis goes much further and is the final element of the roadmap. This is a vast area with enormous potential for further value enhancement. Offline big data will form the top level of industry 4.0 and will enable the greatest improvements. However, in order to reap these benefits, it is imperative that all previous steps of the logic of the roadmap presented here have been implemented.

The data collected should cover all aspects of the process and be available in sufficient quantity for the use of big data analysis. If the protocol is followed correctly, Offline Big Data will serve two main functions. First, to find and solve the known process-related problems. In addition, machine learning is used to identify problems and help create new solutions and countermeasures.

Offline analysis will indeed be a powerful tool in the hands of process owners and top management, as it will enhance process knowledge with new information that has not yet been identified. The analytical technology of the future can be divided into four main categories:

  • Descriptive analysis: It helps people understand what exactly happened when an event occurred, why it occurred, what went wrong and where it happened in the process.
  • Diagnostic analysis: It enables staff to find out how the event occurred. This comprises events ranging from deviations to delays in a production line. In these cases, the diagnostic analysis shows the basic causes that led to the problem.
  • Predictive analysis: it allows users to assess what might happen next. This is a critical step in the industry 4.0 context when IT systems like MES, with its powerful data analysis algorithms, can predict future events and allow users to make corrections to avoid expected events before they actually occur.
  • Prescriptive analysis: IT applications such as MES help users understand what needs to be done. These features are deeply rooted in the IoT (Internet of Things) and the application's ability to compare scenarios, create patterns, and find one or more plausible solutions to current or predicted problems.

This marks the end of the roadmap to digital manufacturing. Planned, systematic and incremental changes to the ongoing process, supported by reliable and operational IT applications, will be the key to fully digitized manufacturing. Industry 4.0 is deeply embedded in IT and related technologies: a challenge that typically exceeds the comfort zones of many manufacturers. Finally, you should take two key pieces of advice from this article:

  • 1) To successfully implement digital manufacturing, follow this roadmap.
  • 2) On your way to Industry 4.0, rely on industry and IT experts who specialize in MES applications.

About Critical Manufacturing

Critical Manufacturing Germany GmbH is based in Dresden and develops software for the production industry. The Manufacturing Execution System "Critical Manufacturing MES" offers far-reaching possibilities for integration into the industry 4.0 ecosystem and increases performance, control and quality in complex manufacturing organizations. The company is part of the Critical Group, a private group of companies founded in 1998 that provides IT solutions for business-critical applications.

This article was first published by Industry of Things.

Original by Jürgen Schreier / Translation by Alexander Stark

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