MPDV's Four-Stage Model supports manufacturing companies of all sizes and industries on their way to the Smart Factory. (Source: MPDV, Adobe Stock, Photocreo Bednarek)

Four Stages to the Smart Factory – Filling the Model with Life

Numerous companies have already set out to transform their production into a Smart Factory – some with success, others with painful setbacks. This begs the question: Why did the latter companies fail and what can they do better? MPDV’s Four-Stage Model describes a promising strategy for the transition into a Smart Factory.

The model developed by MPDV is based on a direct approach geared to the needs and requirements of the company in question. This means that the factory must first gain transparency to become more responsive. Transparency and responsiveness enable self-regulation, which in turn will lead to the Smart Factory if combined with interoperability. In the following, we will first explain the distinct stages of the model and the steps towards the Smart Factory. In the second part of this article, you can find out what MPDV has to offer to help manufacturing companies make progress towards the Smart Factory.

Stage 1: The Transparent Factory

How do you create transparency? Quite simply, by understanding and visualizing processes, collecting data, and evaluating this data in a targeted manner. Experience shows that key figures and dashboards are perfect tools for clearly presenting complex relationships in the manufacturing environment. Stage 1 is about showing employees and management how well production and the supporting processes are running, where problems occur, opportunities for improvement and what can be optimized. The online monitoring of production and all ongoing activities result in a digital image of production.

Stage 2: The Reactive Factory

The next stage is to utilize transparency to make processes more robust and at the same time more responsive. Employees must be empowered to enable processes to react to external influences and malfunctions without compromising efficiency. We speak of real-time capability as the reaction should be direct without delay so that no time is lost, or machines continue to produce faulty products. The available data helps regulate processes and plan orders in detail. The aim is to assign pending orders to machines and to factor in other resources such as tools, materials, energy, and production staff. Stage 2 also includes digitally supported maintenance and quality management. The final objective of all measures is to boost efficiency and reduce production costs.

Stage 3: The Autonomous Factory

By automating the planning processes, you enter the third stage on the way to the Smart Factory. In addition to detailed planning, other processes can be automated and mapped as control loops. The simplest form of self-regulation consists of monitoring a measured value and initiating countermeasures as soon as the value is outside of a defined target value range. A countermeasure can be an individual instruction for production employees or an automated action that is instantly executed without human intervention. As a result, applications for the decentralized control of production processes also feature in stage 3. The role of the „augmented operator“ is assigned to humans in the autonomous factory. In this role, people use the wealth of information to intervene in self-regulation if the system is unable to find an effective solution. Data from stage 1 and planning results from stage 2 support people in better understanding the complexity of production processes. The same applies for the supporting processes.

Stage 4: The Smart Factory

The last step on the way to the Smart Factory looks at the bigger picture. This involves networking existing systems in such a way that data can be correlated, leading to new insights for optimizations. An example is the networking of production and the supply chain to react faster to requirements arising from processes. Useful partner systems of the manufacturing IT are not only the ERP system, but also a product life cycle management (PLM), warehouse management system (WMS), or facility management. Some industry-specific requirements can only be realized if these systems cooperate. As a result, product and component traceability can be achieved throughout the entire value chain. Another useful aspect is the networking of applications down the value stream to monitor all influences on production.

MPDV’s IT solutions for the Smart Factory

So how can MPDV help manufacturing companies to tackle the four stages and move closer to becoming a Smart Factory?

MPDV develops and sells manufacturing IT: the Manufacturing Execution System (MES) HYDRA, the Advanced Planning and Scheduling System (APS) FEDRA, and the Manufacturing Integration Platform (MIP). MPDV’s appified applications can be easily assigned to specific use cases and to the relevant stage of the Four-Stage Model:

  • Stage 1: To create transparency, the MES HYDRA collects data in the shop floor and displays it in evaluations. Most mApps of the HYDRA X categories Order Management and Resource Management are among the applications that should be implemented in stage 1. If required, mApps of the category HR Management can be used to create transparency when it comes to working times of employees. Stage 1 typically deals with MDC, PDC, and simple data collection as well as KPIs and dashboards.
  • Stage 2: The Planning tool APS FEDRA supports reactivity. The tool can be used to plan simple operations and even complex order scenarios. If combined with maintenance management in HYDRA X, planning can also integrate upcoming maintenance activities. Even workforce planning is included in APS FEDRA. The integration of further resources such as tools, material, or energy into detailed planning can already be realized in stage 2, but many companies wait to implement these features at a later stage.
  • Stage 3: The next step is to implement automatisms. APS FEDRA can support the automatic planning process with artificial intelligence. In order to achieve satisfactory results, the default values must be correct, and all relationships must have been mapped in the system. Not only planning, also maintenance management of machines and tools can be automated. For this to work, create control loops based on monitored process parameters. The same applies for material management: the calculation of material availability helps to avoid interruptions due to a lack of material. HYDRA X then controls all the necessary material movements and, if necessary, transfers them to a connected automated guided vehicle system (AGV). In a production with multiple product variants, mApps of HYDRA X Assembly Management help you to master the complexity and provide employees on the production line with the information they need.
  • Stage 4: When it comes to interoperability and collaboration, the Manufacturing Integration Platform (MIP) plays a major role. All mApps from MES HYDRA X and APS FEDRA are based on this integration platform and the networking of the various mApps becomes clearly evident. For example, energy consumption can be correlated with order data to find out whether an order consumes more energy than usual. This information could in turn trigger maintenance. The measures of stage 4 also include the connection of facility management or product development systems, for example product life cycle management (PLM). Along with the automatic import of NC programs, it is also possible to transfer inspection characteristics from CAD data of the PLM system. If you take part in the MIP ecosystem, you can add mApps of any provider to your manufacturing IT and thus increasing efficiency and transparency.

At all stages, Artificial intelligence (AI) can help to exploit available data more effectively. mApps of the AI Suite offer a wide range of applications.

The experts from MPDV recommend to also use Change management. Manufacturing companies thereby ensure that the planned measures are accepted and supported by all parties involved. At the start of the project, it is primarily the management that has to commit to the project, but as the project progresses, the involvement of employees at all levels becomes increasingly important. If these basics of change management are observed, excellent results can be achieved.

Lean & IT paves the way to the Smart Factory

Transforming your company into a Smart Factory can only be accomplished if the right IT solutions are implemented and the right lean methods are introduced. Focusing on value creation, or in other words what you want to invest, is crucial to this endeavor. Because only what creates added value is truly “lean”! Consultant from Perfect Production are happy to support you!

Experts from the MPDV Group seamlessly pave the way to the Smart Factory and ensure successful implementation in the end. MPDV’s Four-Stage Model is thought to be a guide for all manufacturing companies wishing to implement the Smart Factory. Unfortunately, there are no shortcuts.

 You can find further information about the four stages towards the Smart Factory in our white paper.

Author: MPDV GmbH

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