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Digital Transformation

Digital transformation represents a strategic endeavor encompassing the integration of digital technology into every facet of an organization. This comprehensive process assesses the organization’s processes, products, operations, and technological infrastructure to pinpoint opportunities for enhancing operational efficiency and accelerating product deployment to market.

Often referred to as Industry 4.0 or the fourth industrial revolution, organizations must embrace the imperative of establishing agile frameworks capable of adjusting to continuous change and uncertainty, inherent elements of corporate life. Through this approach, they will bolster their capacity to navigate rapidly evolving technologies such as state-of-the-art artificial intelligence (AI), machine learning, and integrated IIoT (Industrial Internet of Things). These advancements will profoundly influence the strategies and goals of digital transformation endeavors.


Artificial Intelligence

Artificial Intelligence (AI) refers to a machine’s capability to execute cognitive tasks commonly linked with human intelligence, including perception, reasoning, learning, environmental interaction, and problem-solving. Examples of AI technologies encompass robotics, autonomous vehicles, computer vision, natural language processing, virtual agents, and machine learning. AI is generating value for industries by enhancing the skills of knowledge workers, particularly engineers. These applications primarily leverage AI’s predictive prowess. Businesses are adapting traditional challenges into scenarios where AI can employ machine learning algorithms to analyze data and experiences, identify patterns, and offer recommendations.

It’s understood AI serves as a potent force for both disruption and competitive advantage. Contact IAS today, and let’s initiate a discussion concerning your organization and how AI can enhance your Overall Equipment Efficiency (OEE) while providing deeper insights into your production processes and equipment performance.

Machine Learning

Machine Learning (ML) is a branch of artificial intelligence that studies algorithms able to learn autonomously, directly from the input data. Some of the benefits of ML:

  • Improved quality control
  • Lower production costs
  • Improved product design
  • Better employee safety
  • Better supply chain management

One of the manufacturing sector’s most impactful applications of machine learning is in vision-based part inspection and process monitoring. By employing affordable sensors like RGB cameras coupled with machine learning algorithms, organizations can achieve efficient part inspection with high throughput. Integrating vision, including image and video analysis, with machine learning facilitates comprehensive product monitoring throughout the production cycle. Moreover, a vision-based approach enables continuous, high-quality process monitoring. IAS has successfully implemented numerous vision projects designed to improve quality, reduce cost and increase productivity.

Vision Manufacturers Supported

  • Cognex
  • Keyence
  • Optel
  • Seavision
  • Systech

Industrial Internet of Things

Successful IIoT integration requires the ability to make it possible for independently created software systems and data to communicate. IIoT integration requires taking a mix of new IIoT devices, IoT data, IoT platforms, and IoT applications and combining them with IT assets; making it possible for them to transfer information back and forth with each other seamlessly, resulting in a well-optimized end-to-end IoT business solution.

Given that end users engage in diverse industries across various platforms, the potential for technical variations is extensive. Rely on IAS to examine the array of technologies to identify optimal strategies for your application.

IAS’s team is proficient in providing comprehensive IIoT solutions from start to finish. Our experienced engineers manage PLC programming, communication protocols, backend applications, and frontend user interface development. We excel in configuring cloud solutions customized to the specific needs of the application.


  • Identify/specify IIoT devices/systems
  • Determine communication protocol
  • Identifying data sources
  • PLC/controller programming
  • User interface(s) application development
  • Project management
  • Control panel design and construction
  • Commissioning
  • Complete documentation package
  • Ongoing service and support