The future of manufacturing powers transformation across multiple industries. Furthermore, every touch point in the factory of the future will be digitally connected, making the entire manufacturing process one connected organism that is highly responsive and adaptable.

By 2020 60% of manufacturers will have embedded digital technologies to support up to 30% of revenue.

The smart factory integrates technology into the manufacturing process. Therefore increasing speed and accuracy – making the process more efficient, environmentally friendly and ultimately lowering costs.




In truth, AI and Machine Learning make the biggest impact. Large amounts of data is collected and processed at high speeds. Certainly, iterative learning makes the system increasingly intelligent. Subsequently this information is embedded in business platforms improving operations.


Notably there has been increased interest in Robotic Process Automation (RPA) and Autonomous Indoor Vehicles (AIVs) within the manufacturing industry. The term cobot, coined by Northwestern University in the USA, refers to robots working alongside humans. Essentially, these bots take on tasks that are extremely complex or too dangerous. At this time much research is being done in combining semantic systems and industrial automation. Basically, semantics is the study of meaning, closely related to Natural Language Programming (NLP) and Artificial Intelligence (AI). In essence when applied to robotics the possibilities for automatic reasoning and high-level interactions are endless.


Engineering simulation software is becoming part of the manufacturing process to mitigate errors and therefore save time and costs. Specifically simulating the manufacturing process from start to finish. This enables manufacturers to accurately predict weaknesses and errors. Furthermore enabling continuous improvements in the foreseeable future.  


Innovation within quality control hasn’t seen much progress up until now. To date it has been the job of humans to do random checks. Certainly this is very time consuming and unreliable. Manufacturers now prefer using embedded metrology. Metrology measures all components in the production process, allowing for a continuous quality control check at every step.


An innovation that will replace the use of robotics in electronics manufacturing is light-based manufacturing. Optoelectronic tweezers use light to move objects around within liquid to primarily produce components for smartphones and computers. This nano manipulation technique makes electronics manufacturing less expensive. Fulfilling the need of the Internet of Things revolution by producing at scale.


Lastly, the innovation to make the greatest impact is quantum computing. Quantum computers are able to process many values and assess all possible scenarios at once. The system immediately discards scenarios that are not ideal. The speed at which industry is accelerating is inconceivable at this stage. The predicted horizon line for maturation is around 25 years. By 2030 quantum computing is expected to be a $50 billion market as the first generation machines are released and used primarily for Research and Development.


Product Engineering

Principles used in the field of engineering is applied when software products are engineered and developed.

Machine Learning

ML, a category of algorithms, assists in making software applications more accurate


Simply put automation is what makes a system or process function automatically.

Internet of Things

“Anything that can be connected, will be connected” – Guido Jouret. This quote sums up what IoT is.

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