Defining the lean logistics learning enterprise: Examples from Toyota's North American supply chain.
Bibliographic record
Abstract
Lean manufacturing, as based on the Toyota Production System, is frequently attempted in manufacturing facilities all over the world. In order to reap the true benefits of the lean philosophy, it is necessary that firms expand their lean thinking beyond their own doors. This dissertation looks at lean logistics as the next logical step. First, lean logistics is defined based on the principles of the Toyota Production System, as a logistics system which seeks to shorten lead time by eliminating all of the varying wastes in the system. The philosophy of lean logistics is described using the analogy of a house comprised of a roof, walls, and a foundation (based on the Toyota Production System house). The roof represents the goal of the logistics system. The walls holding up the roof are just-in-time delivery and quality systems. The foundation is made up of the operational systems necessary for the proper functioning of the just-in-time delivery and the quality systems. To complete the house, respect for humanity is located in the center. Examples from Transfreight, Inc. are used to illustrate the definition of lean logistics. Transfreight is a logistics company originally formed as a joint venture at the behest of Toyota to serve as Toyota's sole inbound logistics partner for the vehicle assembly plant in Cambridge, Ontario. Transfreight is at the center of Toyota's transfer of its just-in-time philosophy to North America. Transfreight, which uses the lean manufacturing philosophy in all of its operations, now serves many Toyota plants in North America as well as other customers. Second, to consider a broader perspective of logistics systems, a conceptual model of logistics is developed and seven case studies of logistics systems are placed in the model. The first of the models' two dimensions is the scope of the supply chain that a firm considers when it attempts to optimize its value chain ranging from a single link to a supply chain. The second dimension is whether the firm focuses their improvement efforts on the technical systems or takes a sociotechnical systems approach. Most logistics research falls toward the single link end of the continuum and takes a purely technical systems perspective. In contrast Toyota's approach views the supply chain as a sociotechnical system integrating people, process, and technology. Finally, lean logistics is placed in the framework of the learning enterprise. Here, the logistics systems of Toyota, Ford, and CAMI (a GM-Suzuki joint venture served by Transfreight) are evaluated for their use, or failure to develop, learning characteristics. The ability to successfully learn is arguably the critical competitive advantage for long-term sustainability of an enterprise.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".