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Production Data Collection (PDA): Definition, Characteristics, Goals

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Definition and Objectives of a PDA System

As we continue the march towards Industry 4.0, it is becoming clear that collecting and utilizing quality data will be critical towards success in the new production age. Collecting high-quality data not only helps create insights that allow manufacturers to improve productivity and profitability, but it is also an essential first step towards the high-tech, data-driven manufacturing industry bearing down on us.  

While there are already many systems that let companies collect, analyze, and rapidly act upon data coming off the shop floor, indicators are that they only capture a small portion of the production process. Estimates are that less than 5% of machines and shops are digitally monitored, with the primary emphasis being on end-stage or high-value processes. 

But suppose data from the shop floor will contribute towards an innovative, highly competitive production process. In that case, more effort must be made to acquire a pool of data that is representative of the entire production process. This is where production data acquisition, and its related tools, are vital.  

What is production data acquisition?

Production data acquisition (PDA), also called BDE or PDC, data collection about a company’s processes. It is the deliberate monitoring, tracking, and collection of production or operating data in ways that make it useful and relevant in attaining macro production or productivity goals in an organization.  

PDA’s purpose is to collect data that helps make the production process leaner, more flexible, and sustainably more profitable. Although the past half-century has witnessed incremental innovations that have allowed manufacturers to reduce waste and variability while dramatically improving quality and yield, there is still some way to go. Variability in the manufacturing process remains a fact of life in several industries, such as mining, pharmaceuticals, and chemicals.  

As McKinsey notes, “the sheer number and complexity of production activities that influence yield” in these industries require “a more granular approach to diagnosing and correcting process flaws.” Even in industries where best practices have become standardized from all input stages to the final product, PDA still offers significant benefits.  

How we understand and apply best practices is based on evolving knowledge about the relevant industries and the science state at the time. But as we increasingly push the bounds of what is possible by applying novel and game-changing technologies, it is essential to maintain a granular understanding of manufacturing processes and where the most significant improvements can occur.  

McKinsey believes collecting and exploiting high-value data about the entire production process, or incremental segments at least can help companies assess and improve their production practices. Current data collection measures in multiple industries already enable an abundance of real-time shop floor data. When this is combined with a PDA system that can collect and aggregate this data in the most meaningful manner across the entire production spectrum, organizations can begin to enjoy their data’s true value.  

By implementing a PDA system, companies can gain greater transparency in the production process. They can learn more about quantities, qualities, and times or operational production processes. With this heightened transparency and fine control over the process, they can isolate the most significant production process elements and continuously improve these components. They can also achieve greater control over the costs of production, ensuring the organization can sustainably grow.  

What is operating data in production?

PDA is all about collecting data about production processes. But what types of data exactly are relevant for collection through a PDA system? In these cases, we are referring to operating data.  

Operating data in an organization is the total organizational and technical data that contributes towards or is produced during the production process. This data takes many forms and includes order, personnel, machine, and process data. Before we consider f each of these data groups’ elements, it is crucial to understand why the emphasis is on operating data.  

As we have mentioned above, organizations are increasingly enjoying access to an abundance of data. Daily, massive data streams are produced from the shop floor in many forms, including electronic, automated, and manual. However, not all of this data may be useful for improving the production process. Some of the data being collected may be about events that are not useful for assembling important information or deriving valuable insights. As a result, it is necessary to be confident that you track and collect the right data.  

Order-related data in the PDA process includes manufacturing data such as qualities, quantities, weights, counts and times. It also provides order status, work progress, confirmation of work performed on individual operations. This data group represents the elements relating to the origination of orders and the start of the products’ lifecycle.  

Personnel data includes data relating to shop floor labor, such as working hours, access control, and assembly line responsibilities. It also includes working hours, attendance, and actual work performed on the line.  

Machine data covers all of the data relating to the core of the production line activities. It includes switching frequency of machines, interruptions, duration, and production quantities. Moreover, it covers faults, messages, service staff interventions, maintenance data, consumption of materials, temperature, and other statistically significant data points.  

Lastly, process data tracks process parameters, design modifications, quality analysis, testing, and similar data points.  

What is a PDA system?

A PDA system facilitates the collection, storage, and transmission is data relating to the entire production process. It can be said that a PDA system aims to automatically collect production data that is generated during the processing of production orders and associated operations.  

The data can either be recorded directly via the machine control system or in manual form. A worker transmits status or quantity messages to the PDA system via a terminal in production. Of course, it is more desirable to implement an automatic data acquisition and storage system. Manual data acquisition only increases the possibility of errors and reduces worker productivity.  

Using a PDA system, the recorded data can then be transferred to a PPS (production planning system) or ERP system (Enterprise Resource Planning). The bi-directional data transfer occurs in real-time and thus creates a valid and consistent data basis for all other production control systems.  

The PDA’s accurate data leads to more realistic target times, which has a tremendously positive effect on planning orders and resources. Also, the automation of the PDA should minimize the risk of errors.  

Finally, the automatic PDA also reduces the employees’ workload, since no more notes have to be filled out and delivered by hand. The employees can concentrate more on their core tasks. Thus, the right PDA system forms the basis for calculating key figures such as Overall Equipment Efficiency (OEE) and a multitude of evaluations that can be used to optimize the production process. 

Characteristics of a PDA System

A modern PDA system should have specific characteristics to ensure optimal efficiency. 

  • Ease of Use: The usability or user-friendliness of the PDA system is decisive for the user’s acceptance. If the BDE system is intuitive to use, it can support the user in his work in an optimal way. This ensures that the data is correct and forms a valid basis. 
  • Technology: Another essential characteristic is the currency of technology. When technology is outdated, every expansion becomes a risk. Unfortunately, as every smartphone user knows, technology becomes obsolete very quickly. Thus, even BDE systems that were modern a few years ago are already very outdated today. Today’s systems must be web-based and controllable from any end device. At the same time, they have to offer high performance to handle any data volume. 
  • Implementation: The PDA system must guarantee a fast and smooth performance to avoid delays and additional costs. 
  • Flexibility: A sound system must, above all, be able to collect a wealth of data. Therefore, error-free data acquisition is the most critical feature. The system may need to collect data on material usage, quality controls, complaints, and many other factors. Therefore, it must be ensured that it can cope with current and future requirements. The PDA system must guarantee a fast and smooth implementation to avoid delays and additional costs. 
  • Interoperability: Data collection must be compatible with existing business systems. This is because a lack of interoperability with ERP systems or other IT systems that should have access to the data poses a significant risk to future security. 

Implementing an effective PDA system

Capitalizing on the wealth of data available to organizations starts with implementing an effective PDA system. With the characteristics above in mind, manufacturers should begin by considering the data already available to them. Are these data pools useful for improving production outcomes and the overall process?  

If they are not, then focus should shift towards strategizing on ways to secure data collection at source. Common strategies include the use of RFID tags, sensors, and other data collection and transmission technology. The task of collecting data from scratch can be resource-intensive, though. Leaders at these companies may explore taking a long-term focus to invest in the right practices and systems, including exploring the merits of an incremental approach.  

For manufacturers that already have a wealth of data available, the task will be to invest in the systems and skills that will allow proper exploitation of this data to optimize existing processes.  

In both cases, there should be specific emphasis on monitoring the most relevant data points representing the whole manufacturing process. With the bird’s eye view that this data provides, leaders at the organization will be better positioned to spot, analyze, and quickly react to the data’s insights.  

PDA should be carried out in a standardized, consistent, and reliable manner. This means relying on automated PDA systems from equally reliable solutions providers. At FORCAM, we provide a cloud-hosted, turn-key solution that meets manufacturers’ PDA requirements, both big and small. Contact us to learn how we help manufacturing companies collect big data in the production process and turn it into actionable insights.