Process optimization by the user for users

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Our mission: A data-driven process optimization in production

From users for users: Team leader Uwe Knappe on the three most formative factors in the development of advanced data management (adm)

Data and its application are an indispensable, increasingly important success factor for industrial manufacturing in the 21st century. The right data in the right place at the right time is what makes process optimization in production possible in the first place. Read here what we have learned from our customers during the development and how we apply this experience back to customer projects.

Objective setting, as-is analysis, programming, testing, roll-out, adaptation: Flexible and efficient solutions for data-driven process optimization in production needs years of development. We have already gone through these steps. In our adm, we are guided by the requirements of our customers worldwide and welcome them on board.

In 2002, thyssenkrupp Automation Engineering broke new ground as a machine builder

The adm development team and its head Uwe Knappe have succeeded in building digital solutions that collect and visualize important system data in the production line and trigger improvements. Uwe Knappe can still remember the start of adm in 2002. Even before adm was developed, we were already supplying vehicle manufacturers (original equipment manufacturers, or OEMs for short) with assembly lines for their plants. At that time, our customers mostly used their own quality data systems and machine data acquisition systems. We had to saddle up to that. Then, at some point, we said to ourselves: We can also implement such systems ourselves! We then got the necessary resources for the development of a data-based production management software. Mind you, this was in 2002: half a decade before the first iPhone came onto the market. This allowed us to add the development of our own digital systems to our service portfolio. Since then, we have also delivered our assembly lines with the technology we developed, which we have continuously optimized over the past 20 years. This example shows very well how we are actively participating in the digital transformation and Industry 4.0.

3 formative factors in the development of adm

At thyssenkrupp Automation Engineering, and especially in the adm development team, we have repeatedly stumbled across situations since the start of development that we have had to learn from and rethink and optimize for. Large international vehicle manufacturers (original equipment manufacturers, or OEMs for short) are as diverse as they are demanding. So we have learned a lot in practice for adm since 2002.

1. We take our own approach to the collection and analysis of data

The key to a successful manufacturing execution system (MES) is that it must help link information technology (including ERP systems) with operation technology (including the shop floor). adm makes quality data and measured values from the operation technology segment available to the information technology segment. This way, they are also passed on to the workers, production managers and process experts.

In developing our Machine Data Analysis (MDA) module, we opted for our own simpler approach than that taken by our long-standing customers. They usually rely on control-heavy systems. Machine data is passively tapped at adm, and all evaluations and interactions take place on the MDA module side. This relieves the control side.

Where other providers saw the solution in several systems for quality data management (QDM), we chose road down the middle for our QDM module. It records both binary values (OK and NOK criteria) and detailed results, such as real measured values or screw curves.

2. The incentive for innovations are our customers and their assembly lines

To put it more simply: We have a lot of experience, because we have implemented many different projects worldwide. That's why we already knew many of our customers' software requirements for industrial manufacturing when we started development. The motto "From user for user" is lived practice: Since we integrated adm for a pilot project in one of our customers' plants in 2003, we have been continuously gathering know-how. This way, we continue to improve our system. A constant exchange of experience is indispensable for this.

3. Every system has potential for improvement: we continuously optimize and expand

Since the first adm integration in 2003 - a pilot project for a vehicle manufacturer producing in Hungary - it has become clearer to us with each subsequent customer: There is no perfect system. Only a good one, which we continuously adapt and improve. This is the only way to ensure that it always meets changing requirements.

Customers can use our standard web client to query evaluations of key data such as malfunctions, piece counts or overall equipment effectiveness (OEE) within an assembly line or the entire plant, and to obtain information on how to improve their production. In this way, the different requirements of our customers for the presentation of these key figures provide us with indications for optimization, which we will include in the adm standard in the future.

Because we are in constant exchange with our customers, we learn better and better how to assess what adm has to achieve. And where there is still a need for optimization. In the future, an additional component for the MDA module will monitor components, stations or assembly units and determine maintenance cycles (for example, the filling levels of hydraulic fluid). In the event of predefined triggers (for example, when time intervals are exceeded or a certain number of produced parts is reached), it will inform the maintenance colleagues, who will then take action.

We have been collecting and analyzing data for many years. Long before the term 'Industry 4.0' existed.
Uwe Knappe, Head of adm development team at thyssenkrupp Automation Engineering

Process optimization and production 4.0 is about collecting and evaluating the right data in the right place at the right time.

The future is fast approaching, and it is becoming increasingly digital: Industrial manufacturing is inconceivable without digitally controlled, comprehensively networked and robot-assisted automation. In the midst of all this future, however, we should not forget: The past helps to shape it. Every work process and every assembly station produces a large amount of data, which is the basis for a very targeted continuous improvement process (CIP). Every analysis refers to past developments and aims to improve them in the future.

In essence, Industry 4.0 for a system like adm means:

● Networking of all systems involved: Data sources and sensors work independently and proactively in even greater numbers. Even without downstream controls, they can provide your data on machines and components via networks and promote rapid evaluation and processing.

● Support through digital applications: Solutions like adm collect and visualize essential production data. They help your human "colleagues" make data-based decisions.

● Cases of decentralized decisions: Networked systems are already capable of autonomously controlling processes, but they still need to be programmed by the human user to do so. Assembly lines - equipped with a production management system (PMS) under human supervision - (almost) completely control themselves.

Digital transformation is not an end in itself. Systems like adm are designed to make production processes on the assembly line more efficient. And thus ultimately make work easier for each individual worker. All modules and components are the result of an analysis of production conditions on site. In the process, we gain experience from our customers' plants all over the world: process optimization "from the user for the user".