Why Aeronautical Industry Needs to Employ Prescriptive Analytics Tools?

prescriptive analytics

prescriptive analytics

Can leveraging Prescriptive analytics help organizations inch towards Industry 4.0?

Industry 4.0 is here and ready to transform every single industrial sector and aspect business framework. While data shall continue to be an essential cog in this pipeline, it is not just about automation and data exchange. In fact, it also includes the network of cyber-physical systems, the Internet of things (IoT), cloud computing, and cognitive computing. In terms of business operations, Industry 4.0 aims to enable an organization with predictive & proactive maintenance, early warning detection, proactive planning and risk management, enhanced customer experience, and automation of monotonous and standardized tasks. However, for this, one has to access and analyze data to gain meaningful insights. With the daily explosion and expansion of data, there arises new challenges along with it. And without timely awareness about how to tap the data for its lucrative benefits, companies are going to lag in the competitive race. Hence it is high time they leverage prescriptive analytics.

Prescriptive Analytics is a form of advanced analytics which examines data to provide optimal recommendations during a decision making process. It determines ways in which business processes should evolve or be modified. Though it is related to both descriptive analytics and predictive analytics but accentuates actionable insights rather than data monitoring. It can help businesses to identify data-driven strategic decisions and avoid the limitations of traditional data analytics practices. This includes fatiguing valuable resources on housing data that does not inform business decisions and missing out on new distinctive revenue streams and insights. It aims to find the best solution, given a variety of choices. Further, it empowers organizations to make proactive decisions to optimize the outcome of future events or risks and provides a model to study them. In brand marketing its scope goes beyond the sales conversations. Basically prescriptive analytics is the future of analytics and shall also power Industry 4.0.

While every industrial niche has been adopting prescriptive analytics to augment its functions and offerings, the aeronautical industry has been far behind in the race. Although this sector has embraced technologies like CAD, 3D printing, additive manufacturing, AI, it is slowly yielding the benefit of data analytics. For instance, big data analytics and text mining techniques help this industry understand the customers’ sentiments and other maintenance issues. By understanding this data, airline companies can boost customer satisfaction and increase airline revenue.

Recently, it has been proposed that prescriptive analytics can also transform the aeronautical industry with its potentialities. This is backed up in the research carried out by Tamara Borreguero and collected in her Ph.D. dissertation, “Scheduling with limited resources along the aeronautical supply chain: From parts manufacturing plants to final assembly lines” (whose directors are Álvaro García and Miguel Ortega, founding partners at baobab soluciones). Her thesis suggests three ways in which prescriptive analytics can be leveraged to solve the bottlenecks of this sector. For each of these challenges, a mathematical model and a practical application were developed, which validated the usefulness of the approach adopted in each case.

The first solution was proposed to solve the airframe manufacturing short-term scheduling. Next was mid-term scheduling for airframe manufacturing to correctly size the productive capacity and comply with the delivery schedule. And the third suggestion was about dealing with short term scheduling for final assembly lines. This is crucial to keep operations in each of the workstations in compliance with the cycle time (takt time) and enable the least possible consumption of resources. Optimizing the scheduling is a key aspect of the digital transformation of the aeronautical industry and improving its supply chain network. This research thesis, demonstrated how prescriptive analytics could bring practical implications that align with the objective to be a part of industry 4.0. It concluded that prescriptive analytics could be a key to transforming the supply chain of the aeronautical industry and help transition towards the 4.0 paradigm.