Understanding the shopfloor side of a use-case is crucial for successfully expoiting the data. Our team offers years of experience and deep expertise in production technology.
Real data from production can be "ugly" and partly unstructured. We solve this challenge and don't stop until we extracted the maximimum information out of your data.
Working with us means getting the best possible return on investment. You will neither find another offer nor in-house resources being more cost-efficient than us.
E.g., for: Predictive Quality, Process Optimization.
E.g., for: Predictive Maintenance, Energy Management.
E.g., for: Defect Identification & Evaluation.
Software products like the ones of IconPro help industry customers with their individual needs on their cloud and AI journey.
We are happy to support IconPro as a Microsoft Partner with profound expertise in industrial AI.
Working with IconPro in a pilot project proved to be simple, efficient and focused right from the beginning.
IconPro Apollo just met our demand for on-premise condition monitoring and analysis of our measurement machines.
IconPro‘s combined deep expertise in production technology and industrial software development is very convincing.
We utilize the IconPro Apollo software for predictive maintenance of our robot systems to minimize downtimes.
OGP provides Multisensor Inspection Systems.
We utilize IconPro Software to bring to our customers
IconPro became a strategic partner for the application of machine learning on our energy management use-cases.
With the help of IconPro TSAF we process energy carrier data from our factories to identify energy waste and reduce costs.
IconPro already did a great job when it first came to investigate the relations and potential in our production.
With IconPro software, machine learning can be utilized directly by our process engineers to predict & optimize quality.
Aufgrund seiner Erfahrung ist IconPro ein zuverlässiger Partner für Machine Learning Software, die den tatsächlichen Bedürfnissen in der Produktion entspricht.
IconPro Apollo erweist sich als intelligente, vernetzte und produktive Lösung für die smarte Überwachung von Messmaschinen.
IconPro demonstrated the ease-of-use of the ARES software for deriving predictions and optimizations from production data.
For our new e-mobility production line, we integrate predictive quality with IconPro from the beginning.
Vom ersten Treffen an machte IconPro einen außergewöhnlich innovativen und professionellen Eindruck.
Wir waren beeindruckt, wie schnell die IconPro ARES Software wesentliche Prozesseinblicke generiert.
Having started with a larger software engineering project, IconPro became the main external partner for our AI strategy.
With IconPro, we enable the users of our statistical process control software to react to changes before they get critical.
What is Data Analysis in Production?
With the advent of automation, Big Data and predictive analytics, manufacturing companies are gaining valuable insights that can help them improve efficiency, reduce costs and improve quality. By analyzing their process and quality data, manufacturers can identify trends, spot anomalies and better understand how their processes work. This approach can help manufacturers make smarter decisions, develop better products and ultimately increase their sales and profits.
Data Analysis in Production refers to the systematic examination of data collected from a variety of sources within a manufacturing company, from receiving, to engineering and manufacturing, to quality assurance, as well as shipping, service and customer feedback. It is designed to help companies make informed decisions to improve their operations and achieve their business goals.
How is Data Analysis in Production being utilized?
In the manufacturing industry, data can come from a variety of sources, including machines, sensors, production systems, and enterprise resource planning (ERP) systems. The data collected can be used to measure key performance indicators (KPIs) such as production efficiency, product quality and equipment effectiveness.
Data Analysis in Production can take many forms, including descriptive statistics, predictive modeling, machine learning, and statistical analysis. By using these techniques, manufacturers can gain insight into their operations, identify areas for improvement and drive continuous improvement.
To ensure that results are accurate and meaningful, it is important to focus on data quality. Poor data quality can negatively impact data analysis results and lead to incorrect conclusions and decisions that can actually worsen the baseline.
To achieve high data quality, organizations must implement robust data management practices, including data validation, cleansing and normalization. Data validation ensures that data meets required standards for accuracy and consistency, while data cleansing removes all errors, duplicates and irrelevant data. Data normalization ensures consistent and standardized data, which is essential for accurate and meaningful analysis.
What are typical use cases of Data Analysis in Production?
What are the benefits of Data Analysis in Production?