The Chart Looked Fine But the Parts Did Not
Photo by Sam Moghadam on Unsplash
A fictional workplace story about a real quality lesson
On his third week as a supply chain analyst, recent BBA graduate Evan Miller thought he had found a way to make his new boss’s Monday easier. The Michigan factory where he worked made small metal brackets for vehicle seats. Evan had built statistical process control (SPC) charts to track the size of brackets coming off one machine. Every point sat comfortably within the chart’s control limits.
Then final inspection sent back another cart of parts.
“Too many brackets outside the customer’s size requirements,” the inspector told him.
Evan checked the chart again. No spikes. No strange pattern. No warning. He printed it and walked to Megan Larson’s office.
“The machine looks fine,” he said, sliding the chart across her desk. “Why are we still getting rejected parts?”
Megan, a University of Michigan-Flint BS in Supply Chain Management graduate, studied the chart. “This tells me the machine is behaving consistently,” she said. “Did you check whether it’s capable?”
“Capable of running?”
“Capable of making brackets within the customer’s specifications, even with its normal ups and downs.”
Evan paused. “I checked the control chart.”
“That’s a different question,” Megan said. She drew two lines on a sheet of paper to mark the smallest and largest bracket the customer would accept. Then she sketched the spread of the machine’s measurements. The spread went past both lines.
“Your chart asks whether the machine is doing something unusual,” she explained. “It isn’t. Unfortunately, its usual output includes bad parts because the normal variation in its output is too much. Process control charts only detect abnormal variation, they have no idea about user specifications and whether the normal variation is small enough or not.”
Evan stared at the sketch. “So the process is consistently missing the mark?”
“Exactly. How did you learn satistical process control (SPC) without learning this first?”
He winced. “Process capability was a short section near the end of a long SPC chapter. I spent so much time calculating chart limits that I didn’t give it much thought.”
They went to the floor together. With a technician, they found a loose guide that let the bracket shift slightly as the machine worked. The technician tightened it and recalibrated the machine’s feed settings. Evan gathered a fresh set of measurements. The spread was now narrow enough to fit within the customer’s size requirements. Only then did his charts become useful for watching whether the improved process stayed that way. Final inspection confirmed the next run met the specifications.
“So the chart wasn’t wrong,” Evan said.
“No,” Megan replied. “We were asking it to answer the wrong question.”
That distinction shapes how we teach Operations Management at UM-Flint. Operations management textbooks (such as Krajewski and Malhotra, Heizer et al., and Stevenson) tend to present SPC and its charts in detail and leave process capability to a short section at the end of the quality chapter. At UM-Flint, we flip that teaching sequence. Students first learn to ask whether a process’s natural variation can fit inside customer specifications. Then they learn how SPC charts help determine whether the process is stable and monitor it after improvement. A control chart can show that a process is steady. It cannot make an incapable process produce acceptable parts.
UM-Flint students practice that decision in the right order so they never make Evan’s mistake. They are taught to always ask: Is the process capable? After all, it does not make sense to control a process that is not capable.