Style Sampler
Layout Style
Patterns for Boxed Mode
Backgrounds for Boxed Mode
Search News Posts
Genel Sorular 850-244-11-22
•
Destek 850-244-11-22
Mühendİslİk Çözümlerİ
We optimize your production processes ensuring you are more able to make efficient use of machines, avoid production downtime and increase the quality of your products. To do this we use the most advanced Big Data and AI technology available. We use your company’s machine and production data as a database for our analyses which we can also access and process for you if needed. We also build on your own experts’ knowledge and experience and incorporate it into our analyses.
This is how we guide you on your tailored path to Industry 4.0 and the “digital factory”. Within the “digital factory” products or parts including their components, processes and data are called “digital twins” and are typically made available on IoT platforms. Cloud-based solutions such as these cannot, however, be used universally: In application scenarios requiring high latency and data protection it is often more advantageous to use decentralized data processing and distributed learning. This is where “Edge Computing” provides computational power where needed. Our software architecture and decentralized learning experts help you develop the most suitable solution for your individual circumstances.
If Machine Learning is to be applied to production, we develop a systematic procedure model by integrating relevant domain and specialist knowledge into an automated form. This is then applied to the data analysis by adapting learning procedures to typical production issues. Our long-term experience creating time series analyses and using technology building blocks for image and audio analytics combined with our intensive decentralized learning research gives us a technological advantage when production-ready solutions need to be developed quickly.
Working in cooperation with you we can develop new digital utilization models which will allow you to hire out your machines and to bill your customers based on their usage.
Data collection is not the only issue, though. Additionally, you must model and refine the data to conform to the chosen algorithms. One of the problems with machine learning that is regularly encountered is data security. Security is a crucial issue that must be addressed when a corporation has retrieved data. To use machine learning accurately and effectively, it is crucial to distinguish between sensitive and non-sensitive data. Companies must store sensitive data by encrypting and putting it on other servers or in a location with complete security. Reliable team members can be given access to less sensitive information.
With recommended actions, the operator can improve maintenance cycles based on condition, reduce spare parts costs and prolong the remaining useful life (RUL)
Identify areas of optimization potentials to increase efficiency and productivity of the plant.
Due to increased connection and distant accessibility, data security and reliability are major problems. There is great concern about harmful parties gaining access to private information. But for newcomers, investing in and maintaining expensive security software might not be possible.
Our data analytics services provide a significant advantage to chemical engineering firms by allowing them to optimize their processes, improve efficiency, reduce costs, and increase profitability. Our data analytics services for chemistry engineering include:
Using data analytics to monitor and optimize chemical processes can help companies identify inefficiencies, reduce waste, and improve yields. This can be achieved through the use of sensors and data analysis software that can provide real-time data on various process parameters such as temperature, pressure, flow rate, and chemical composition.
Data analytics can help chemical engineering firms to improve their quality control processes by identifying patterns in data that may indicate quality issues. This can help them to identify potential problems before they become significant issues, reduce waste and rework, and improve overall product quality.
Data analytics can be used to predict equipment failure, allowing chemical engineering firms to schedule maintenance proactively rather than waiting for a breakdown to occur. This can reduce downtime and repair costs, as well as increase the lifespan of equipment.
Data analytics can help chemical engineering firms to optimize their energy usage by identifying areas where energy is being wasted or used inefficiently. This can help them to reduce their energy bills, improve sustainability, and reduce their environmental impact.
Data analytics can help chemical engineering firms to optimize their supply chain by analyzing data on suppliers, inventory levels, and customer demand. This can help them to improve their procurement processes, reduce lead times, and improve customer satisfaction.
Data analytics can help chemical engineering firms to ensure compliance with regulatory requirements by providing real-time data on environmental conditions, chemical usage, and emissions. This can help them to avoid fines, reduce environmental impact, and maintain their social license to operate.
We offer a variety of services for Engineering data analysis:
If you're looking for a reliable partner to help you unlock the power of genetic data in engineering, look no further than anaplatform. Contact us today to learn more about how we can help you advance your research efforts and improve engineering outcomes.
anaplatform Big Data offers appropriate technology and solutions for all sectors. Until today, Software Houses, GSM, Insurance, E-Commerce, Bank - TSM, Automobile, Education, Payment Systems, Robot Industry - guided missile etc. and served in many other fields.
