%%viewer [https://player.vimeo.com/video/670136295]/% __Type of tool:__ web application __Required skills: __ - Knowledge of process parameters - Knowledge of material properties - no programing or data science knowledge needed __Short description of the tool: __ The tool offers a guided selection process for quality assurancetechnologies to be implemented in the production process. Therefore, it offersan intuitive web frontend with a series of selections to define your processand process problem. Before you get started, take a look at the [guidelines|https://di-plast.sis.cs.uos.de/attach/Sensor Tool/Di-Plast_Tool Guideline_Sensor_fin.pdf|style='background-color: rgb(255, 255, 255);'][|https://di-plast.sis.cs.uos.de/PageInfo.jsp?page=Sensor Tool/Di-Plast_Tool Guideline_Sensor_fin.pdf|style='background-color: rgb(255, 255, 255);' class='infolink'] and make yourself familiar with how to use the tool. __Use case/problem:__ searching for sensor to monitor a certain process problem __Description of the problem the tools solves:__ There are usually two kinds of process or product quality problems. The ones you can solve by changing process parameters and the ones that show up rather random wih no visible link to process or material parameters. For the later the only solution is to monitor those problems and sort out the affected parts __Disclaimer:__ __Access the tool directly:__ [Sensor Tool|https://share.streamlit.io/skz-digi/diplastsensorselection/updated/main.py|style='background-color: rgb(255, 255, 255);'] __Contact person of the tool: __Christoph Kugler __Related tools:__ - Analyse and Visualize your process data with data analytics -> [Data Analytics] - Get guidance to set up a working data infrastucture -> [Data Infrastructure Wiki] - Improve internal information and material flow -> [VSM] - Match material requirements with material properties -> [Matrix]