Data is an essential component in making a smart and digital factory. 

What methods are used to control manufacturing data? 

  1. First method: Installing IoT devices on the machines in order to learn their behavior. 
    • Requires hardware installation and maintenance. 
    • Implementation of this method is expensive.
    • The manufacturing system becomes more complex as a result.


  1. Second method: Turn existing data which has already been accumulated during your manufacturing process into smart information (Data already collected data from machines, sensors, automated tests, IT system ERP/MMES):
    • Can be done remotely and does not require hardware installation.
    • Supports changes in the data.  
    • Cost of implementation is significantly lower than the first method. 

The Digital Factory has been established in the industry for many years.
For each process to be monitored and focused, the data must be unified to create a unified harmonized database that “speaks” ONE LANGUAGE.  Digital Factory provides tools for planning factories in virtual reality and models.

Usually companies do that by developing an API for each source of data. The problem with this API methods that it takes a very long integration and service time.

The outcome of that is that you may collect a lot of data during your manufacturing process BUT the majority of the data is not used as smart information to control the manufacturing process and optimize quality and effectiveness. 

The digital factory has allowed companies to innovate while reducing complexity, turnaround time, and costs.

QualityLine recognized this challenge and developed a better value solution based on multivariable manufacturing data. 

We call it a Holistic view – an End-to-End control system that requires no maintenance, no API, and provides valuable analysis within weeks.

In order to develop a unique data collection method, QualityLine invested years in research and development. With the AI/ML pattern recognition technology we developed, we are able to unify any data at the customer’s facility. Additionally, our data unification solution can analyze all manufacturing processes, utilise all types of manufacturing data, and combine it all into one unified and harmonized global digital twin database. 

By having access to this information, our customers are able to gain global end-to-end control, monitor problems at their manufacturing facilities and improve their processes. 

For example, we can:

  • Detect anomalies of quality and efficiency issues
  • Predict failures
  • Manage end-to-end control dashboards
  • Conduct Field Performance Analytics

Substantial improvements in first pass yield indicate that defect rates decline with increased quality.

Our goal is to enable our customers to improve their manufacturing efficiency and productivity by providing them with the tools to have full control and transparency over their manufacturers.


Tsahi Petel,  VP, Client solutions