The concept of data collection, what are the common data collection methods?

Data acquisition (DAQ) refers to the automatic collection of non-electric or electric signals from analog and digital units under test such as sensors and other DUTs, and sending them to the host computer for analysis and processing. The data acquisition system is a combination of measurement software and hardware products based on computers or other dedicated test platforms to achieve a flexible, user-defined measurement system.

Production data. Intelligent manufacturing is inseparable from the support of workshop production data. In the manufacturing process, CNC machine tools are not only production tools and equipment, but also the node of the workshop information network, through the automatic collection, statistics, analysis and feedback of machine tool data, the results are used to improve the manufacturing process, which will greatly improve the flexibility of the manufacturing process and the integration of the processing process, so as to improve the quality and efficiency of the product production process.

The Gallup MDC system helps companies solve this problem.

Manufacturing Data Collection & Status Management (MDC) is mainly used to collect the working and running status data of CNC machine tools and other production equipment, realize the monitoring and control of equipment, analyze and process the collected data, and also provide data support for other software such as MES and ERP. The MDC system is the integration of the machine tool data acquisition system and the machine tool data analysis and processing system, and is a workshop application management and decision support system with data acquisition, machine tool monitoring, data analysis and processing, report output and other functions. [1]

Through the intelligent integration with the CNC system, PLC system, and the electronic control part of the machine tool, the MDC realizes the automatic execution of the data acquisition part of the machine tool, without the manual input of the operator, so as to ensure the real-time and accuracy of the data. In terms of data mining, MDC provides enterprises with more professional analysis and processing, personalized data processing and rich graphical report display, and statistics and analysis of key data related to machine tools and production, such as start-up rate, spindle operation rate, spindle load rate, NC operation rate, failure rate, equipment comprehensive utilization rate (OEE), equipment productivity, parts qualification rate, quality percentage, etc. Accurate data is transmitted in a timely manner and dispersed to relevant process departments for processing, and the production dynamics of the workshop are guided, responded to and reported in real time, which greatly improves the ability to solve problems and promotes the process of intelligent manufacturing in the enterprise workshop.

<> common data collection.

There are questionnaires.

Consult information, field inspection, and experiment.

1. Questionnaire survey: Questionnaire survey is the most commonly used method of data collection, because its cost is relatively low, and the information obtained will be more comprehensive.

2. Access to information: Access to information is the oldest way of data collection, and you can get the data you want by consulting books, records and other materials.

3. Field investigation: Field investigation is to go to the designated place to do research, which refers to going to the field to conduct an intuitive and partial detailed investigation in order to understand the truth of a thing and the development process of the situation.

4. Experiment: The advantage of experimental data collection is that the accuracy of the data is very high, and the disadvantage is that the uncertainty is great, regardless of the period of the experiment or the results of the experiment.

1. Questionnaire survey

The structure of the questionnaire refers to the order and distribution of questions between groups of questions used for different purposes and between different questionnaires used for the same study.

The steps to design the overall structure of the questionnaire are as follows: first, according to the results of operationalization, the variables are classified, the independent variables, dependent variables and control variables are clarified, and a list is made; Secondly, for each variable, the interview question or interview group was designed according to the interview form. thirdly, the relationship and structure of the interview are planned as a whole; Finally, the auxiliary content of the questionnaire was designed.

2. Interviews and surveys

Interview surveys are surveys that collect data through question-and-answer interactions between interviewers and interviewees, and are used in almost all survey activities. The interview method has a certain code of conduct, from the full preparation of the interview, the smooth entry, the effective control to the end of the interview, each link has certain skills.

3. Observation and investigation

Observational surveys are another method of collecting data, using sensory organs such as the observer's eyes and other instruments and equipment to collect research data. Preparation before observation, smooth entry into the observation site, observation process, observation record, and smooth exit from observation are all highly skillful links.

4. Literature Survey

First, to obtain literature through searching; second, to read the literature obtained; Thirdly, the literature was annotated, summarized and excerpted according to the operational indicators of the research question. Finally, a database of literature surveys was established.

5. Trace investigation

Big data research is also about grasping the relationship patterns between things. In social surveys and research, the investigation of big data is more about selecting data from big data, and it is also necessary to operationalize research hypotheses and variables before the survey.

Data acquisition technology is widely used in various fields. For example, cameras and microphones are all data collection tools.

Generally speaking, data collection should collect as much data as possible from data sources such as target objects, devices, and services, and transmit and summarize the obtained data to the designated area for storage in the form required, so as to lay the foundation for future data mining and analysis.