Manufacturing Data Management

Credit: Irwan Iwe


Medical device manufacturing companies constantly look for ways to streamline production and data management. A company’s ability to innovate is crucial in creating efficient production systems, and manufacturing data is critical to the success of this process.

Revenue in the medical device industry has increased to $50.4 billion between 2016 and 2021. Since more individuals are seeking medical care, the demand for medical devices has increased significantly. 

As demand continues to rise in the healthcare industry, so does the need for accurate manufacturing data. Let’s take a closer look at what organizations can do to bring clarity to manufacturing data management.

The Challenge of Manufacturing Data Management

The seven major components of manufacturing data are:

  • Data collection from multiple sources
  • Data analysis to filter out errors
  • Arranging data sets to improve clarity
  • Storing vital data that will aid in decision-making processes
  • Storing data consistent for use
  • Provide context for the data
  • Analyze the data for instant action

Many manufacturers rely on self-developed data management systems that are outdated when compared to modern management systems. Outdated systems lead to inconsistent data and unhappy clients. Even different departments within the same company may have distinct data collection methods.

Manufacturers must develop a uniform data model to incorporate the systems that function independently of the manufacturing process. Think about the consequences of cataloging a product incorrectly and mistakenly sending it to distributors. This kind of error results in dissatisfied customers and damages the reputation of the manufacturing company.

Poor data management costs the average company $20 million each year. Poor data quality costs the U.S. about $3.1 trillion per year. 

To reduce costs in real-world manufacturing procedures, companies should strongly consider implementing risk mitigation measures, which would help to avoid the following situations:

  • Marketing and product staff may find it difficult to update or search for data using discrete data management systems
  • Lack of sales tools such as demos, flyers, price sheets, and pamphlets, making it difficult to boost sales
  • Unreliable product and stock supply information, driving customers to spend their money with competitors
  • Inconsistent product portrayal, which paints the brand in a negative light across different media

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The Importance of Agility in Manufacturing

An agile organization is able to perform data collection while enriching the data. Data enrichment infuses information from the manufacturing process into the gathered data to facilitate analysis. This process aids decision-making, helping the manufacturing company arrive at the best decision for the business.

The desire to improve agility led to the rise of the Industrial Internet of Things (IIoT). Also known as Industry 4.0, this new phase of the Industrial Revolution focuses on automation, real-time data collection, machine learning, and interconnectivity. 

Industry 4.0 allows manufacturers to remain agile in critical aspects such as:

  • Equipment
  • Automation
  • Quality
  • Maintenance
  • IoT capabilities
  • Manufacturing Execution Systems (MES)
  • Statistical Control Process (SPC)

The objective is to avoid data overload, as unenriched data does not facilitate better decision-making.

Agile organizations are able to make quick decisions, which improves the results of the manufacturer. A lengthy decision-making process can cost a company a significant amount of money. It is extremely important for businesses to have access to clear and concise data – to prevent data dumps that are in effect useless.

Manufacturing Data Management

Credit: National Cancer Institute


Agility Challenges in Manufacturing

A common challenge for agile organizations in manufacturing is a concordance between your information technology (IT) and your operational technology (OT). For instance:

  • It can be challenging to match up OT and IT data
  • It is difficult to examine OT and IT data simultaneously
  • IT and OT data may contain conflicting or contradictory information
  • It can be nearly impossible to arrange the data in a context that would assist process improvement efforts

The challenges posed are not indicative of insufficient data. Instead, they point to the inability to provide context for the operational and floor data required for decision-making.

In reality, the ability to contextualize manufacturing data is just as important as the actual data itself. Industry leaders understand the importance of harnessing data insights to make effective decisions for the organization.

Inadequacies within the infrastructure of manufacturers pose extreme challenges for these manufacturers. For example, the data collected may be too broad or vague to extrapolate insights that would allow for the contextualization of said data. 

As a result, the infrastructure is unable to facilitate the following processes:

  • Data acquisition
  • Provision of adding context and polishing data
  • Collection and integration of data
  • Data analysis and data interpretation

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Key Performance Indicators in Manufacturing

Top manufacturing organizations reported high marks in key performance indicators (KPIs). These KPIs include:

Time to Market: Accelerated Time to Market has a direct impact on the agility of the organization and provides a competitive advantage.

Quality: Higher quality products are indicative of manufacturers that emphasize continuous improvement.

Industry leaders have placed significance on the integration of both IT and OT data. The importance of integration has been the topic of some debate. Some manufacturers believe integration efforts should become a singular unit. Others postulate integration should harmonize with the organization’s processes.

When top industry performers recognize the importance of investing in the right platforms and data management systems, the result is better business outcomes. Applications such as Manufacturing Execution System (MES) have proven instrumental in the successful transition to Industry 4.0.

The need for integration does not end with the manufacturing company. To be fully prepared for Industry 4.0, integration should extend to both suppliers and consumers. Again, integration is no easy task. It requires significant effort and a substantial commitment on the manufacturers’ behalf for successful implementation.

manufacturing data

Data Management in the Medical Device Industry

The medical device industry in America is worth approximately $140 billion. Although the medical device market continues to grow, unit costs may decline over time. Since the medical device industry is highly regulated, unanticipated regulatory issues could become a cause for concern.

One way to remain competitive in the healthcare industry is to continuously differentiate products. Integration plays a role in the ability of an organization to differentiate products. 

Manufacturing Data Solutions

When it comes to selecting a suitable partner to help manage your manufacturing data in the healthcare industry, you need one that is Industry 4.0 ready. Working with RBC Medical not only simplifies the development of your medical device, it also streamlines the manufacturing process. 

Our team has over 25 years of experience guiding projects from conception to completion, which is why more than 93% of our clients return to us for repeat business.

Contact us today to find out how to accelerate time-to-market your medical device by prioritizing speed, dependability, and flexibility.

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