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Connecting the lab
How to connect your laboratory
Connecting a testing laboratory to the digital world involves integrating various instruments and data protocols into a unified IT system. This guide outlines practical ways to achieve efficient data management in labs, focusing on the adoption of B2B SaaS solutions and IoT technology. It aims to support labs in the digital transformation process, ensuring that they can leverage their data for innovation and quality control while overcoming integration challenges.
In manufacturing, where precision and efficiency are crucial, the role of data-driven decision-making is undeniable. It serves as a key factor for enhancing operational efficiency, thereby offering a competitive advantage across various domains, including polymer processing, engineering or coatings. Today, the adoption of B2B SaaS solutions and IoT technology is transforming data management practices.
This principle also holds true for material development and quality control in the material testing lab, where data can serve as a foundation for innovation and discovery. However, laboratories and their respective IT departments must go to great lengths to integrate their instruments and data protocols into a unified IT infrastructure that can actually streamline processes and obtain data-driven insights. It is often a daunting task to connect your material testing laboratory to the digital world. In this guide we show ways on how lab instruments can be connected to bring efficient data management in the material testing lab.
Software for getting your laboratory online
There are a range of software tools on the market that can assist with a lab going digital. It depends on which tasks you would like to have resolved.
The most common tool in the lab is the Laboratory Information Management System, or LIMS. It streamlines laboratory operations but also introduces challenges alongside its benefits. It enhances sample management, automates workflows, and centralizes data management, aiding in regulatory compliance and quality control. However, a significant amount of IT resources are required for its introduction, maintenance and for implementing process changes. The initial setup, especially integrating laboratory instruments, can be resource-intensive and may require specialized training for users, increasing reliance on IT support. Additionally, many LIMS systems come across as not being very user-friendly, which makes their acceptance in the lab difficult.
Material testing labs also frequently use Computer-aided quality assurance (CAQ) programs, designed to enhance quality management in manufacturing. A CAQ automates quality control processes, improving product quality and process efficiency, while also ensuring compliance with industry standards. This automation facilitates the integration of quality data with other production systems, enabling informed decision-making and early defect detection, which in turn reduces waste and costs. However, implementing a CAQ system comes with significant upfront costs, including the expenses for software, hardware, and staff training, and requires continuous system maintenance. The complexity of tailoring the system to specific production needs can be a major hurdle, requiring specialized expertise. Resistance from employees accustomed to traditional quality management methods can also further slow down adoption. Organizations must balance these pros and cons to determine if CAQ is the right choice for their requirements.
Out of the box, a CAQ systems cannot communicate with laboratory instruments to automatically collect data and minimize manual entry errors, whereas LIMS is not very user friendly so can take a lot of time and/or specialist help to integrate into your laboratory.
A data management solution provides a structured approach to organizing, storing, and analyzing an organization’s data, bringing both significant advantages and notable challenges. The centralization of data under such a system is a key benefit, making critical information readily accessible across departments. This may not only include laboratory data, but also production parameters, recipes or a material data base for raw materials used.
The complexity of tailoring the system to specific production needs can be a major hurdle, requiring specialized expertise. Resistance from employees accustomed to traditional quality management methods can also further slow down adoption.
This accessibility improves collaboration and more informed decision-making. Moreover, the emphasis on data quality is another advantage, with built-in tools for data cleaning and validation ensuring the accuracy and reliability of the data used for business analytics and strategic planning. The automation of routine data tasks not only reduces the likelihood of human error but also frees up valuable time, leading to gains in operational efficiency.
However, as with other tools, such a system needs to be configured to meet the specific needs of the laboratory. Furthermore, the successful deployment of a data management solution typically demands substantial training for staff, which can temporarily affect productivity. Having said that, tools like LabV are easier to implement, are scalable and provide a user-friendly modern interface that increases acceptance and simplifies the transition. While this system shares some functionalities with LIMS and CAQ, these systems are more focused on collecting data and are user-friendly. As we will see below – while most of the tools are also dealing with the same issues, some like LabV have a technology that connects every device in the material testing lab and will seamlessly integrate into existing infrastructure without being a major IT project.
| Data Management Platform | LIMS | CAQ | |
|---|---|---|---|
| QA/QC functions | + | + | +++ |
| Process Efficiency | +++ | ++ | ++ |
| Instrument connectivity | +++ | + | + |
| Scalability | +++ | + | + |
| Cost | +++ | + | + |
| UI/UX | +++ | + | + |
| Integration with broader IT infrastructure | +++ | ++ | + |
Table: Comparison of LIMS, CAQ and data management systems
Connecting your material testing laboratory to the digital world
Now that we are familiar with the software options for automating and digitizing the laboratory, let’s now explore the mechanisms behind these integrations.
The three most common ways to connect your instruments to the digital lab are as follows:
- Via file export — exporting of the data to a readable file format, e.g., .csv, .xml, Excel.
- Via a database — storing the data in a database to make it accessible from there.
- Via web interfaces — storing the data on a server or in a cloud application to make it accessible from there via REST API.
Now that we are familiar with the software options for automating and digitizing the laboratory, let’s now explore the mechanisms behind these integrations.
The three most common ways to connect your instruments to the digital lab are as follows:
- Via file export — exporting of the data to a readable file format, e.g., .csv, .xml, Excel.
- Via a database — storing the data in a database to make it accessible from there.
- Via web interfaces — storing the data on a server or in a cloud application to make it accessible from there via REST API.
Why is it so compliated to connect my lab?
While it all sounds easy, connecting disparate software tools like CAQ or LIMS involves a complex interplay of technical and operational challenges. But why is it so resource-intensive? Here’s a breakdown of why:
Data Heterogeneity
Different systems employ varied data formats and standards, requiring extensive effort in mapping and transforming data for compatibility. Semantic discrepancies in data interpretation between systems require complex reconciliation processes.
Integration Complexity
The need to accommodate specific organizational customizations complicates integration, making it hard to apply one-size-fits-all solutions. API limitations and intricate database schemas add layers of technical challenges to the integration process.
Technology Evolution
Software updates can change or deprecate features and modify APIs or database schemas, requiring continuous adjustments to maintain integration functionality. This constant evolution makes keeping integrations up to date a challenging endeavor.
Lack of Interoperability Standards
The absence of widely accepted standards for data interchange magnifies the difficulty of achieving seamless integration, forcing developers to navigate a complex landscape of proprietary formats and protocols.
Innovations to overcome the problem
There is a new connectivity standard on the horizon, called Laboratory Analytical Data Standard (LADS). It is designed to enable interoperability among laboratory and analytical equipment. By leveraging the open communication platform OPC UA, developed by the OPC Foundation, LADS aims to facilitate manufacturer-independent, seamless integration of diverse laboratory devices in a plug-and play fashion. It all sounds great, and LADS may well be a future-proof standard that mirrors the varied workflows across customer industries, however, it will take some time until instrument suppliers have adopted the standard and until every instrument in the lab is equipped with it.
While LADS is certainly the right step forward, it may take some time. In the meantime, LIMS, CAQs and data management solutions will continue to struggle. One innovation, however, is the patented mapper of LabV which is a computer-implemented process for efficient instrument connection. It works in three steps:
1. Receiving laboratory device data, which is delivered by various laboratory instruments in mostly heterogeneous formats
2. Converting the received data into a homogeneous target data format
3. Saving the homogenized data in a central database for further processing
The outcome is that the integration of all lab devices is neither that costly, nor does it require a huge amount of IT resources. All the data is united in one database that can be easily connected with other IT infrastructure such as ERP or MES systems. Such a comprehensive data management platform allows labs to have artificial intelligence (AI) at their fingertips for simplifying and handling data during routine day-to-day analysis. Unlike other solutions, scientists can now gain access to previously inaccessible data without having to manually search for it or possess the programming know-how to delve into the data manually.
Lab integration made simple
Digitizing a material testing laboratory is a complex endeavor due to diverse systems and data formats. Traditional tools like LIMS and CAQ offer robust features but come with integration challenges and require significant IT investment. LabV emerges as a user-friendly alternative, enabling simpler integration with existing lab processes and IT systems without extensive resources. Its automatic mapper technology facilitates device connectivity, reducing both costs and complexity.
While standards like LADS promise future ease in interoperability, current solutions like LabV provide practical and immediate benefits for laboratories aiming to harness the power of digital transformation. This shift towards streamlined, data-driven operations is essential for laboratories to maintain a competitive edge in an increasingly digital world. So, whether you’re involved within the polymer & plastics, metals and metal products, 3D printing/additive manufacturing, engineering, grinding, or battery manufacturing industries, LabV can help to optimize and streamline your laboratory analyses and quality control efforts.