Developed as a graduate capstone, the software aims to connect box and pallet specifications to assembly-line demands.

A box can protect a component in transit and still create problems on the factory floor. It may be too heavy to handle, too large for a rack or too small to hold the parts needed between deliveries. For manufacturing engineers, those competing requirements turn packaging into a production-planning decision.

Olasubomi Akanbi is developing PackSpec to help engineers work through those requirements before specifications are agreed with suppliers. The application is the subject of his master’s capstone in logistics systems engineering at Bowling Green State University in Ohio, drawing on a packaging problem he encountered during a material-flow engineering internship on the Tesla Semi programme.

The idea is to give engineers a common starting point for decisions that otherwise move back and forth between suppliers, packaging specialists and production teams. A working version has been built, Akanbi reports, while a browser-based version is in development. Its effectiveness remains to be established through evaluation.

Turning production requirements into packaging rules

The problem became apparent when supplier proposals had to be checked against assembly-line needs. A configuration that worked for shipping could provide too few parts at the workstation or use space inefficiently. Resolving those mismatches meant revising proposals and reviewing them again.

PackSpec brings several of those checks into one workflow. Engineers upload an Excel file containing part numbers, dimensions, unit weights and quantities required per vehicle. They then enter production rates, stock coverage and rack-lane settings. The intended outputs are recommendations for parts per box, box dimensions and pallet layouts.

The link to production demand is central. Rather than treating a container as an isolated object, the application sizes boxes around the quantity of parts a gravity-flow rack lane needs to hold for four, eight or 12 hours of production. That connects a physical packaging choice to how quickly the line consumes its contents.

The capstone’s stated rules include maximum box dimensions of 30 × 30 × 12 inches, a 30 lb box-weight ceiling and one box type per lane. Pallet configurations must use complete layers on a 52 × 50-inch pallet, with a 1,500 lb load limit for delivery by an autonomous mobile robot, or AMR.

Those figures describe the application’s specified planning conditions. Their value is in making the requirements explicit: fitting more parts into a box is useful only if the result also meets the handling, storage and transport limits. For engineers reviewing a supplier proposal, a shared set of rules could make disagreements easier to identify and resolve.

Experience at the point of use

Akanbi’s internship at Gigafactory Texas in Austin ran from January to May 2026. His material-flow assignment covered semi-stator housing production flows across two factories, including receiving, staging, buffer sizing, route planning, and moving unfinished parts between operations.

He used Revit and AutoCAD to model rack, staging and equipment layouts for more than 250 Semi powertrain parts. He also developed Plan for Every Part records for seven components across three assembly stations, documenting packaging, transport methods, dolly dimensions and picking arrangements.

These assignments placed packaging within a larger system. Container dimensions affect where parts can be stored; the quantity inside affects replenishment; and how parts are presented affects how an operator can access them. PackSpec takes that relationship as its starting point.

Akanbi reports that a part-presentation programme involving packaging, factory design, environmental health and safety, and manufacturing teams increased agreement on proposed designs from 54 per cent to 94 per cent. That reported result concerns the coordination programme and should be distinguished from PackSpec, whose performance has yet to be demonstrated.

A focus on operational measurement

Earlier work at Glovo’s fulfilment operations in Lagos offers another example of Akanbi’s approach. As Technical Product Manager for Fulfilment Centres from April to December 2024, he reorganised storage locations around demand and frequently co-ordered products. He introduced scanning to link products to defined locations.

He reports a 1.48-minute reduction in fulfilment time per order across approximately 600 daily orders, without additional staffing. At that volume, the reduction equates to around 14.8 aggregate hours of order-processing time each day. This time is released across the operation, rather than reducing the length of a working day.

At Unilever in Lagos during 2022 and 2023, his manufacturing and supply-chain assignments included line balancing, investigating product-weight variation and restoring four redundant machines. He reports a 25 per cent increase in machine speed within three months for the restoration work, without capital expenditure. These experiences provide context for the software project’s emphasis on measurable operating requirements.

The next test for PackSpec

The next stage is to establish how reliably PackSpec produces usable configurations. Evaluation must show whether its recommendations meet the stated constraints and how they compare with existing planning methods. Any claim that it reduces design revisions or planning time will depend on those comparisons.

PackSpec remains a capstone application under development. It offers the opportunity to translate a recurring factory-planning problem into software that can be tested against explicit requirements before broader use is considered.

Akanbi, who earned a degree in Industrial and Production Engineering at the University of Ibadan in 2021, is now taking that work forward through his graduate capstone. PackSpec’s usefulness will depend on whether its calculated recommendations hold up in the practical decisions engineers and suppliers need to make before a box reaches the line.