This morning, I read a Bloomberg article titled “Boeing’s Supply Chain Has Become Too Complex” by an opinion columnist. Boeing’s recent challenges have been attributed to its suppliers. The article elaborates on how the scenario is evolving, what led to the current challenges, and what Boeing and its suppliers are doing to resolve the fiasco. The supplier at the center of all this is Sprite AeroSystems Inc., in Wichita, Kansas.

Just like the corporate world dilly-dallies between centralized and decentralized data architectures, it has dilly-dallied on vertical integration for a long time. Another article that I was reading this morning was regarding Sam Altman eyeing semiconductor factories. A software solution company eyeing something like this would have been considered crazy. But I believe it makes sense when the solution in question is GPT.

The reason cited is that there could be a shortage of AI chips towards the end of the decade. My postulation is that sometimes your vision is too strategic to rely on an external partner, no matter how strategic that partner is. Dependence on an external partner would mean sharing the details of the algorithm’s future vision. It also implies not having complete control of the performance of your algorithm since it also depends significantly on the hardware. There are several other reasons as well, but the gist is that the shortage of chips is not the primary driver for this interest, in my opinion.

Like with many other aspects, the problem is that organizations tend to follow the FOMO approach when thinking about strategy. This was true for strategies like whether to keep vertical integration or not, and is now also crucial from the perspective of AI strategy formulation.

Boeing wanted to emulate other industrial manufacturers when it decided to implement the outsourcing model, but as the article highlights, its product is no other industrial machinery. However, this is not the scope of this article. Let us try to understand the core challenges and how AI can help Boeing if they don’t want to change its business model.

The article mentioned in the beginning of this blog summarizes the key issues: “But the latest challenges appear rooted in manufacturing glitches and poor supply-chain management rather than design. Before the plugged door blew open on the Alaska Airlines flight, Boeing had disclosed two separate quality-control issues tied to Spirit: one involving incorrectly installed rear fittings and the other being improperly drilled fastener holes.”

Let us understand the roles that were defined in the supply chain of these aircrafts, with the example of exit doors:

• Spirit was responsible for constructing the exit doors, both the usable ones and the plugged ones. AND doing the initial quality inspection
• Boeing was meant to do quality-control checks on pressurization and seals on its finished planes.
• FAA was meant to double-check each 737 on its way out the door. 

While the drilling defect is a manufacturing and assembly issue, missing these defects during inspections across the chain, as highlighted above, is a supply chain issue. In the second part of this article, to be published on 01/21, we will explore how AI-enabled solutions can help eliminate manufacturing issues, precisely, the issue of incorrectly drilled holes. In the third and final part, we will explore how AI-enabled solutions can help with the supply chain issue of missing quality issues.