Read the full German article how avato is enabling their customer Steinbeis to optimize production processes with the Smart Data Framework as the central part of their Industry 4.0 initiative.
“Faster” and “Better” are the keywords around which the Industry 4.0 project at Steinbeis Papier revolves. With avato consulting as a strategic partner these goals could be achieved. What do you need? 25,000 sensors and the solution tailored by avato, which delivers data from production every second and, in conjunction with data from MES and ERP or other systems on the SAP HANA platform, evaluates it almost in real time with the help of machine learning. But not only the production benefits. The new platform is also used in purchasing, materials management and controlling – other areas are planned.
Click here to watch the video for more information about the project.
avato customer Steinbeis Papier GmbH wins for Industry 4.0 project after the SAP Quality Award 2019 in the category Innovation in Germany also the EMEA Regional Award.
Industry 4.0, IoT, Big Data, AI – just catchwords or ingredients for successful digitalization in medium-sized businesses?
The focus on relevant business results, an excellent team combined with the intelligent use of modern technologies lead to convincing results for the medium-sized manufacturer of sustainably produced recycled paper. The independent international jury of the EMEA SAP Quality Awards therefore awarded the Industry 4.0@Steinbeis project, which was carried out with avato’s support, gold in the Innovation category. Out of all the winning projects of the 15 SAP market units, it was selected as “the best of the best SAP implementation projects” in the Innovation category.
If you want to learn more about the project, Steinbeis Papier and the services of avato consulting, please read on…
UPDATE: EMEA Regional SAP Quality Award Gold in the category Innovation for Industry 4.0 @ Steinbeis
In the middle of 2017 Steinbeis Papier GmbH (https://www.stp.de) chose avato consulting ag as a strategic partner for its digitization initiative under the title Industry 4.0 @ Steinbeis Papier. In a short preparation phase the goals were defined, possible application scenarios evaluated and prioritized for implementation in a roadmap.
The implementation started at the beginning of 2018. The technical platform was set up, more than 25.000 sensors were integrated and the prioritized application scenarios were implemented in several release cycles.
The project led to impressive results for the medium-sized manufacturer of sustainably produced recycled paper. These convinced not only the Steinbeis management, but also the jury of the SAP Quality Awards 2019. The project was initially awarded gold in the Innovation category by SAP Germany in mid-December (https://news.sap.com/germany/2019/12/quality-awards-2019-kundenprojekte/). The jury was particularly impressed by how the joint team of Steinbeis and avato significantly improved production and maintenance processes within a tight time and budget frame through intelligent and innovative use of modern technologies and with a data-driven, agile approach.
UPDATE: At the end of April 2020, the project was now also awarded the Regional SAP Quality Gold Award in the Innovation category. An independent jury selected it as “the best of the best SAP implementation projects” in the Innovation category from all local SAP Quality Award winners from the 15 SAP market units in Europe, the Middle East and Africa (EMEA region) in a multi-stage selection process (https://news.sap.com/2020/04/2019-regional-sap-quality-award-winners/).
In the first project phase, the focus was on optimizing production processes and the value chain. In particular, the early automated detection of unusual events and procedures in the production facilities and the production process delivers significant optimizations in yields and quality, but also helps to prevent expensive machine and plant failures.
Currently, the integrated database from production and business management applications with the analysis and machine learning tools are used to implement various application scenarios in materials management, purchasing and controlling.
The solution used at Steinbeis is based on the avato Smart Data Framework. The SAP HANA in-memory database is used to collect the data from the various production and quality systems and to analyze it in conjunction with information from the MES and SAP system. Furthermore, various modern machine learning algorithms and IT tools are used to quickly and cost-efficiently process the large amounts of data into practically usable information.
If you would like to know more about the procedure, the tools used and the experiences, please contact us or browse through our blog.
Start free, grow at low cost
SAP HANA Projects do not have to start with a major investment
SAP HANA, Express Edition (HANA XE) is a slim version of the SAP HANA platform, which, with a few exceptions, offers all important functionalities in a compact and ready-to-use format. With this multimodal in-memory database platform, a wide variety of data can be processed efficiently.
Among the most important modules and functions are:
- Relational DB Engine (OLTP + OLAP)
- Graph Engine
- Text processing module
- Geo-spatial module
- Document Store
- Time Series
- In-database Predictive / Machine Learning
The different engines can be applied simultaneously and directly to your data. The data does not have to be duplicated and managed multiple times between different distributed software components, wich is often the case with other data architectures. This means that even complicated use cases can be tackled quickly and efficiently with a relatively simple architecture.
Furthermore, the platform offers several built-in machine learning, AI and business algorithms. Since these are implemented very close to the data, query response times in fractions of a second – even on mass data – are possible.
The software license enables both non-productive and productive use cases. This means that a HANA XE can be used not only to create prototypes but also to deploy productive applications.
HANA XE comes with all important HANA features free of charge up to 32GB RAM. This allows SAP HANA projects to start with low cost – without lengthy license procurement – and quickly. Especially PoC or pilot projects, as they are almost always recommended in the Data Analytics and Machine Learning area, benefit from the uncomplicated and fast use of the very powerful SAP HANA technology.
If the free 32GB RAM is no longer sufficient, the license can be easily extended up to 128GB with license upgrades from the SAP Store:
Due to the efficient data compression SAP HANA requires significantly less memory resources than conventional databases. Depending on the data and the chosen data model, compression factors of 5-7 are common. Compared to uncompressed CSV data, a factor of up to 15 can even be achieved.
“In the wild” – Examples from the field
In our avato Smart Data and SAP consulting practice, the SAP HANA XE platform has established itself as an all-purpose weapon. avato was able to implement even complex use cases with low budgets by making use of this toolbox. Examples are:
- Master data generation and optimization with ML methods; analysis and processing of SAP transaction data from 10+ years
- Digital Assistants for SAP ERP by replicating master and transaction data from SAP ERP into a SAP HANA XE for super-fast analysis and processing using ML algorithms, and delivering the results to SAP ERP via digital assistant with or without user interaction
- Advanced production controlling applications: material and document flows (e.g. batches) are converted into graphs. Key performance indicators can then be calculated easily using graph analysis methods. Even more complex analyses can be performed by applying graph algorithms to the data
- Advanced production analysis applications: historical and near real-time production data from complex chemical manufacturing processes are represented as graphs together with plant and asset information. Even complex questions can be answered easily using the graph
- Real-time reporting for several business areas (including procurement, controlling, production). The use of Virtual Data Models (VDM) and HANA XSA modelling, as well as analyzing the data ins SAP Analytics Cloud (SAC), allows powerful reporting solutions in a short time and with low effort
We are happy to support you solving your tasks with SAP HANA XE in a smart way.
SAP HANA XE – Start free, grow at low cost
How many people are necessary to operate a paper machine optimally? Due to the high degree of automation, actual operation is possible with a very small production team. Over the last 10 years, some paper manufacturers have increased the production volume per employee by a factor of 10! At the same time, paper production is and remains a complex dynamic process with many possible settings and influencing options in a complex production plant. Due to the high and still increasing number of sensors, a fully manual monitoring of the production process by only a few persons is impossible in practice. As a result, problems in the system or operating settings are often not detected. The consequences are unplanned downtimes and quality deterioration in the end product. In many cases, only time-consuming ex-post analyses are possible. Even though process control systems are offering alarming functionality, the checks made are rule-based using static limits without taking operating mode, grades or changes in settings into account. As a result, end users are flooded with alarms, which is why these alarming functions are usually only used to a very limited extent.
Smart Data Approach:
Fully automated and dynamic monitoring of thousands of process signals and alarms in case of unusual patterns in sensor data allow early identification of problems in production. With this new insight derived from data, downtimes can be prevented and product quality is improved. In the Smart Data alarming system, the normal behaviour of the machine is continuously dynamically derived from historical data, taking into account grades and operating modes. Dependent alarms are summarized and prioritized according to importance. In addition to sensor data, monitoring can also be flexibly applied to other data such as quality parameters or calculated indicators such as raw material consumption etc. Resulting alarms are presented in a user-friendly interface where they can be investigated and processed further by end-users with extended analysis functions.
- Increase of OEE – potentially saving several hundred thousands of euro per year
- Prevention of Downtimes
- Improved quality of the final product
- Predictive maintenance
- Real-time Monitoring
- Dynamic calculation of threshold values
- Consideration of grades and production modes
- Prioritization of alarms
- Automated monitoring of raw material and energy consumption
Production Monitoring 4.0 in the Paper Industry – Reduced downtime, improved quality, predictive maintenance