Now let’s look at the other side of the space industry, the part that most people do not see in the news: the development stage. The commercial space value chain ranges from contractors in enterprises to startups, all providing the software, hardware and service solutions to make these missions and exploration possible.
Like any contractor in the space industry, it’s all about innovation, low cost and best quality to stay competitive. This all starts with digital transformation. While we like to think that most, if not all space companies are completely digital, it is far from the truth. Like any company, digitalization is a process that takes time to implement with the challenge of digital platform integration and costs becoming the key factors. Space organizations must always focus on quality, scheduling, and costs; but today its also creating value for the customer and this is where the digital mindset with AI comes into play. Enhancing the ecosystem of any organization through digitalization leads to better speed and agility, improved integration, leaner models and transparency at every step of the supply & support chain process, all through applied intelligence. AI is now becoming part of the business process, supply chain management, production, and testing. Companies are now also taking note to integrate AI into the core functions of the organization through recruiting, marketing and finance to help build the tools to predict the resources needed to optimize results and compliment production.
AI is all about data science and with large amounts of data, this is fuel for the AI explosion. In the distant past, AI was considered too risky, too expensive, out of reach and only could be found in the future, well the future is now. AI has proven its support capabilities in previous space missions as well as back on Earth with smart voice assistants such as Alexa and Siri. As we explore AI on the business side, we need to focus on one of its basic components called machine learning. Machine learning is based on training through vast amounts of information and determining the right and wrong approach depending on the situation. It is this machine learning that allows AI to focus on the data collected by analyzing and determining insights to efficiency. This will then lead to developing better predictive models to identify problems or evaluating the risk of quality failures in the supply chain within organizations. AI is already integrated with a number of data creation solutions and other technological value adds:
• IoT and active tags. Sensors and transmitters for traceability purposes
• Robotic process automation. New tools aimed at simple, repetitive admin processes
• 3D printing. Prototyping design freedom
• 3D vision. Augmented reality to train operators
• Blockchain. Digitally exchange, validate and certify documents
These tools are already or will be integrated with artificial intelligence to provide the real potential to optimize and create value. Some key areas that we are already seeing this progress in the aerospace industry are on machine learning and visualization OCR to identify processes as they occur in real time, then using predictive modeling to address problems at the earlier stage where it is easier and less costly to fix. Another area, not as critical on the B2B side of the space industry, is open source big data used to understand and gain insights into the customer experience. This will play a larger role as we start to see more space-related services become part of the consumer side, such as the space tourism sector. As the space industry continues to become more digital with new data creation in manufacturing and operational processes, organizations will leverage AI to integrate with other value-added technologies to improve the key areas of customers, operations, and offerings. But as space organizations continue to embrace AI, it is important that they need to understand how to differentiate between using AI to gain insight into their operations versus using AI to develop new products or enhance their value proposition.