Industrial Engineering at the Boeing Composite Wing Center

For quick reading, I’ve highlighted the important bits in each section

Introduction

First, a quick summary of the engineering of an airplane wing. The main load-bearing structure of an airplane wing (also known as the wing-box) is made of up several different components:

  1. The Upper and Lower “Skins.” Also known as Wing Panels. The upper panel is labeled 5 in the diagram below.

  2. The Front and Rear Spars. Labeled as 2 and 3. These are like the “spines” of the wing skeleton.

  3. The Stringers. Labeled as 7. These structures add rigidity to the wing panels (and allow for the movement of fuel between compartments in the wing).

  4. The Ribs. Labeled as 4. These plates line the interior of the wing-box, just like the ribs of a skeleton.

For the Boeing 777X, both pairs of panels and spars are over 100 ft long, and the ~90 stringers can range from 2 ft to 100 ft long. All of these components are fabricated at the Composite Wing Center in Everett, Washington. This was the building that I worked at as an Industrial Engineer from 2019 - 2022.

Below is a photo of a full-length 777X panel:

Because some of the specific details are sensitive, proprietary information, I will have to be somewhat vague about the engineering process. But everything I’m going to share in this case study has been released by Boeing publicly.

Theory of Constraints

I will very briefly touch on a fundamental Industrial Engineering concept called the Theory of Constraints. It states that in order to improve the performance of a system, you must follow these steps:

  1. Identify the system's constraint(s)

  2. Decide how to exploit the system's constraint(s) 

  3. Subordinate everything else to exploit the constraint(s)

  4. Elevate the system's constraint(s)

  5. If in the previous steps a constraint has been broken, go back to step 1, but do not allow inertia to cause a system's constraint.

The intent of the everything I am about to share is for us to answer - “What are the constraints of the system at any time in the future, and what can we do to elevate those constraints?”

Manufacturing Process

Broadly speaking, the manufacturing process for all composite products follows the same general steps (including the components I described above):

  1. Raw material (mostly carbon fiber composite tape) is carefully and meticulously formed into the shape of the part

  2. The part is then “cured” in an autoclave (basically pressure cooked)

  3. Modifications are made to the part (which is now hard and rigid after the cure) to get it into it’s final form

Below is a precedence diagram that visualizes the whole workflow of the manufacturing process. Each box represents a “work cell” - a physical location in the factory where some aspect of the components are added to or changed in some way. Each number (X.Y) represents a unique work cell.

Even though the above diagram seems complex, this is only a tiny fraction of the complexity of the system.

Each one of these work cells requires resources in the form of:

  • Functioning machinery/automation (the machines that make/modify the parts)

  • Required tooling (the tools that hold and transport the parts)

  • Qualified personnel (operators of the equipment and quality inspectors)

  • Sufficient raw material (to create the part) and non-production material

  • Time (anywhere from 2 hours to 12 shifts depending on the part and work cell)

Production Rates

The next subject that we need to address is the required production output. See, every airplane program has something called a “rate ramp”. This is a long-term plan of how many airplanes need to be produced per month in order to meet planned and forecasted customer deliveries. It could look something like this:

Okay, so we have our resources (inputs) and our rate requirements (outputs), now what?

One of my main responsibilities as an Industrial Engineer was to understand the performance capacity of our current set of resources and to figure out whether or not we’d be able to meet rate requirements in the future with that performance. And if not, create a plan for what we needed to do to meet rate. This whole process was called “rate readiness.”

If the current performance of a work cell is not good enough to meet future rates, there are essentially two options:

  1. Improve “flow” (make the process within the work cell faster)

  2. Increase “capacity” (increase the number of machines within the work cell)

Improving Flow

In order to reduce the “flow time” of a work cell, there are a couple things that can happen (however, each have their own drawbacks):

  • We can staff more people to a work cell, however:

    • Some cells are highly automated and adding more people isn’t always effective at improving speed

    • Every part of the company has a tight budget on headcount

  • We can optimize the manufacturing process by implementing new engineering solutions or process improvement activities. However:

    • This takes a lot of time and effort from the engineering teams (my team, as well as research and technology engineers, manufacturing engineers, etc.)

    • These solutions sometimes requires investment into new or experimental technology/processes, making them expensive and risky

Another role my team had was planning headcount for future rates, as well as assessing the potential investment vs flow reduction that these engineering solutions would result in.

Increasing Capacity

In order to increase the “capacity” of a work cell, the following measures can be taken (again, each have their own drawbacks):

  • We can buy additional machines/equipment, however:

    • These automated equipment are extremely expensive (millions of dollars+)

    • More machines requires more people

    • Limited floorspace in the factory

    • Long lead time and disruption to current flow

  • We can staff more people to a work cell. The reason why this also works as a capacity increase is because in some work cells, if we have 4 machines but only enough people to staff 2, then obviously bringing in more people “unlocks” the capacity of those other machines. Another situation is if there are 2 people out sick, then they don’t have enough people to operate one of the machines (i.e., lost capacity); more people = less risk. However, the same drawbacks apply as above.

Rate Readiness

With all this in mind, this chart should make some sense:

Here’s what it means:

  • The blue bars represent the actual amount of time that a panel took to complete in the work cell

  • The solid grey line is the running average of these flows

  • The dotted grey line is the most recent value projected out into the future

    • The drop in the grey line means that we’ve assessed that an engineering project should reduce the flow by several hours on average by rate 10 (10 airplanes per month)

  • The red line is the most amount of time that the panel can take to finish its process in the work cell (based on the rate ramp)

The way that we assess this chart is whether or not the dashed grey line is above or below the red line. If the grey line is above the red, then that means your projected performance for this cell is not good enough to meet the requirements for that rate.

Looking at the chart above, this work cell is projected to meet rate for the rates 5, 7 and 10, but not rates 15 and 25. This means trouble, and something needs more to be done.

This is all fine and good, but this is just one work cell. We need to look at the entire system and do this analysis for each work cell, and find the bottlenecks for each rate. That way we can better prioritize our resources to elevate the worst bottlenecks at the right time.

A consolidated version of this system analysis might look like this:

Where each column is a work cell and each value is the “gap” in hours between the required flow and the projected flow.

By this analysis, A.8 and B.3 are our highest priorities starting at rate 10.

Up till now we’ve only talked about the analyses of work cell flows. But when you consider that we have to take into account the resources of headcount, tooling, and raw material, you start to get an idea of how complex this system really is.

Even then, there are many other complex factors that my team worked to optimize and manage: Part quality, scrapped parts, inventory, logistical constraints, material “expiration”, raw material supply chain considerations, etc., and the interaction effects between all of these things. But discussing all those factors might take an entire book to properly discuss.