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The technical report released by the National Transportation Safety Board, along with the primary flight cockpit voice recorder data and archival interview data, were used as the basis for this case. Other available public data such as news reports were used to round out the synopsis of the case study.

United Express Flight 5925 was a scheduled commuter passenger flight operated by Great Lakes Airlines with a Beechcraft 1900 twin turboprop. It was a regularly scheduled flight from Chicago O'Hare International Airport to Quincy, Illinois, with an intermediate stop in Burlington, Iowa. Drawing from various first-hand accounts (cockpit voice recorder) and secondary evidence (news reports, archival interview data, and online sources) of the tragedy, the case provides a detailed account of the key events that took place leading up to the accident at Quincy regional airport. The case describes how the radio interactions, a jammed door and degradation of situational awareness all contributed to the accident. Through many of the quotes in the text and eyewitness accounts, readers gain an understanding of the impressions and perceptions of the pilots, including how they felt about many of the critical decisions in the last minutes of the flight and the situation at the airport.

When the authors teach this case, the students are required to read it as pre-reading before class. Various readings and materials (see supplemental readings below and Exhibit 3) are made available to students before class, and the instructor can choose to use some of these materials to further explore areas of interest. This case is best explored over a 90-min session but could be expanded to take up one 3-h session. This case can be covered in an undergraduate senior capstone organizational behaviour seminar, any general organizational behaviour class (including introductory in nature), an undergraduate communication theory class or an MBA class that focuses on applied organizational behaviour concepts. It works particularly well in the MBA class, as students with work experience can make the links between the behaviours explored in the case and their everyday workplaces.

This study aims to collect real-time, in situ data from polymer melt extrusion (ME) 3D printing and use only the collected data to non-destructively identify printed parts that contain defects.

A set of sensors was created to collect real-time, in situ data from polymer ME 3D printing. A variance analysis was completed to identify an “acceptable” range for filament diameter on a popular desktop 3D printer. These data were used as the basis of a quality evaluation process to non-destructively identify spatial regions of printed parts in multi-part builds that contain defects.

Anomalous parts were correctly identified non-destructively using only in situ collected data.

This methodology was developed by varying the filament diameter, one of the most common reasons for print failure in ME. Numerous other printing parameters are known to create faults in melt extruded parts, and this methodology can be extended to analyze other parameters.

To the best of the authors’ knowledge, this is the first report of a non-destructive evaluation of 3D-printed part quality using only in situ data in ME. The value is in improving part quality and reliability in ME, thereby reducing 3D printing part errors, plastic waste and the associated cost of time and material.