Machine Data Collection vs. Shop Floor Data Collection

Machine data collection is used to ensure that progress towards complete digitalization is successful. Machines that are networked with each other record, store and evaluate data.

Machine data collection is, therefore, one of the core components in Industry 4.0. In the digital age, where machines are networked with each other, a vast amount of data from the devices is evaluated and visualized, and capacities that were previously not used can be better recognized and tapped.

The data obtained from machine data acquisition can be used and processed for various areas of application:

Machine control:They serve as parameters for controlling the machines
Production planning:Production orders are planned and controlled with them. This is done, for example, by commissioning work in a time window that would otherwise be unproductive
Process optimization:The data serve as a basis for the statistical regulation of processes. For example, machine running times are displayed visually to show productivity or utilization graphically

Machine data acquisition (MDA), which automatically collects information and processes it in real-time, is the foundation for effective production in the context of an intelligent factory.

MDA is one of the components of production data acquisition (PDA). Shop floor data collection is an umbrella term for collecting data and actual conditions as well as processes within a company. Machine data collection is the data source for shop floor data collection. It is used for various purposes, such as controlling processes through automatic and statistical methods or planning and controlling orders from production.

Machine data collection (MDC for short) digitally connects machines, production technology, and data processing (EDP) with each other.

It is, therefore, the process of recording information related to production and manufacturing:

to record,
store, and
make it available

With the digital capture of data, the first step is taken towards digitalizing the entire production process. As the information is automatically collected, stored, and made available, the manufacturing processes become transparent.

What is shop floor data collection?

Production data acquisition (PDA) records and collects actual data. This is done through the states and processes that take place in a company. Especially for companies in the manufacturing sector, it is crucial to have up-to-date production data acquisition to be competitive. PDA provides essential information for production planning and control.

How shop floor data collection works in production

With the help of shop floor data collection, manufacturing companies take a decisive step towards digital transformation in the age of Industry 4.0. The manufacturing company obtains a tangible construct of production only when factual data is available that can be relied on. Shop floor data collection is also the starting point for automating production planning and control.

Since digitalization is advancing more and more and Industry 4.0 is the future, intelligent production data acquisition systems that automatically record production data in real-time are playing an increasingly important role in companies.

What kind of operational data is there?

A distinction is made between organisational and technical operational data.

- Order data: This data is used to monitor the progress of the order. It serves as the basis for the further processing of a product to be manufactured. Production data includes, for example, weight, number, quantity, work progress or order status
- Personnel data: This data provides information about the presence and absence of employees. Particularly when it comes to flexible working hours, this data makes it possible to accurately determine employees’ wages. Personnel data are, for example, working hours, attendance times and wage costs
- Machine data: This includes all information that can be retrieved from a machine. Machine data includes running times, downtimes, malfunctions and utilisation
- Process data: These data include various variables within the production process. They help to stabilize the processes. They include relevant information regarding quality characteristics, process parameters and setting data

What are the tasks and objectives of shop floor data collection?

The most important task of shop floor data collection is to record technical and organisational data. This leads to a transparent overview of the information provided. The PDA is intended to show costs incurred, services rendered, and consumption of resources. Based on this, the PDA leads to important conclusions regarding production planning and control.

The main objective of PDA is to create the ideal data basis for production optimization.

What are the advantages of shop floor data collection?

Production data acquisition, if implemented consistently, ensures that processes run more efficiently in the long term and costs are reduced. This results in companies remaining competitive in the long run.

The benefits include:

All operating data is displayed transparently and clearly
Faults are reported in real time
Risks are minimized
Man and machine are used optimally
Orders can be better calculated
By comparing target and actual data, it becomes clear where there is potential and weaknesses
Customer satisfaction increases because there is more reliable information on deadlines and time limits
Processes are continuously optimized, due to the current data collected by the PDA. Resources are better utilized and productivity increases. As a result, the company can react more quickly and gain a competitive advantage.

Difference between machine data collection and shop floor data collection

With machine data collection (MDC), information is primarily collected on production resources within production.

In contrast to MDC, Production data acquisition (PDA), as the name suggests, collects all possible data from the entire plant. MDC therefore concentrates more on the production area and PDA on the entire operation. With PDA, data on the order, such as the material flow, is primarily recorded. So-called PDA terminals are used to see where and when which order is being processed.

Machine data collection is about generating and passing on ACTUAL data that is relevant to machines and production. Therefore, it is the opposite of order data, which only has the end product in mind and logs the TARGET status, which is the case with shop floor data collection.

For full transparency of processes in a company, it makes sense to use both shop floor data collection and machine data collection. For this purpose, the MDC is used to record the use of resources, and the PDA is used to record the material flow as well as the order situation. Together, they form an unbeatable combination for digitizing all processes in a company and recording them in an Industry 4.0-compliant manner.

What are the goals of machine data acquisition?

The goals of MDC include:

Analyze manufacturing processes
Optimize machine running times
Evaluate machine downtimes
In the event of machine malfunctions, report this to the responsible person via a message, for example, by SMS or e-mail.
Collect data for the continuous improvement process

Machine data includes all data that is generated at a machine during production. Process data arise from information necessary for the operation of a machine on the one hand and is generated by the operation of a machine on the other. This includes, for example, target and actual values of spindle speeds or the power consumption of the machines. Product data provides information about the production process. This includes, for example, the number of pieces produced. Product data also provides information on the status of the products, such as weight, dimensions, or temperature.

Machine data is, therefore, all information provided by a machine.

The machine data that are most frequently used include:
- Production quantity
- Machine utilization
- Running the time of the machines, such as the running times of the main spindle or the feed axes
- If a machine can measure automatically, it can provide the number of parts as information
- Reliability as well as the availability of the machine
- Energy consumption of the machine
- Condition of the machine
Machine data collection makes use of different data sources. It depends on the type of machine, the equipment, and the age of the machine:
- Machines equipped with modern technology, such as digital microcontroller control, record the data online via an interface or are stored on a data logger.
- Machines that are older and therefore do not have an MDE interface can be retrofitted with sensors and controllers. With the FORCE EDGE CONNECT, FORCAM offers a possibility to connect even those not intended for digitization.
With special software programs for machine data acquisition, company-specific data can be easily evaluated. Through the software, it is possible to generate individual analyses and records, which are time-related, of the conditions of the machines.

Typical machine data that are evaluated are, for example:
- How long the machine runs and stops per shift
- How many products were produced during a shift
- Compare the productivity of different shifts

How is machine data collection carried out?

Ideally, the data is transferred from the machine’s control system. This can be done, for example, via a data logger or the OPC architecture. A microcontroller in the machine control or a separate unit with connected sensors is required for the data to be processed automatically. Modern machines usually already have a process-controlled unit that uses detailed information. Special interfaces and software then ensure that the data is forwarded to an ERP, APS, or MES system.

These systems use the data received from the machines to display online, for example, where the products are currently located in production and the current status of production. The combination between the machine data collection and an ERP, APS, or MES system ensures high-quality planning and control. The information now obtained enables the company to draw conclusions about set-up times and throughput times and reduce them if necessary. In addition, the company creates the possibility to reduce half-finished parts in production. This approach has a direct impact on the company’s tied-up capital. On-time delivery to meet delivery deadlines is greatly improved.

The use of machine data is a key factor in quality assurance in production. The use of machine data also makes it possible to increase performance within production. This significantly increases the competitiveness of a company. This can be measured, for example, by the overall equipment effectiveness (OEE).