Notice bibliographique
Résumé
Lean thinking has become a part of North American manufacturing and service sectors. This is occurring in an atmosphere of growing customer demands, heavier reliance upon technology and new environmental challenges. The move to create more agile and responsive organizations has become a global race to perfection and of survival. An ever-expanding list of industries and areas of the economy are moving to become lean. Canadian engineers of many disciplines are being called upon to rise to this challenge, yet most do not receive anything more than a brief introduction to lean through their undergraduate studies. What is lean thinking? Lean is simply eliminating all waste within any process. Waste is anything your customer does not wish to pay for. There are 8 different forms of waste. They are: overproduction, inventory, waiting, transportation of materials, motion, inefficient processes, rework and not using your people’s abilities to the fullest. Leaning an organization is through reducing the lead time between the customer’s request and fulfilling that request. Value added steps are retained and non-value added steps are removed to reduce cost and time requirements. The paradigm has changed for design and consulting engineers. For example, system and machine designs that do not continue to reduce or eliminate the costs associated with not only operation and maintenance but now also setups will undermine the success of those engineers and their firms. This is because lean focuses on the waste of setups within processes. Additional tools such as design for manufacturing (DFM), design for assembly (DFA), design for operations (DFO) and quality functional deployment (QFD) are critical skills in the new paradigm. Developing an organizational culture where individual leadership is widespread, spontaneous and visibly supported is a fundamental lean skill. Entire firms are trained in problem solving skills. All of these efforts, through a consistent method, are to create an enterprise-wide continuous improvement culture. Lean knowledge and the ability to pass it on to others are the fundamental skills that Canadian engineers need to be successful. Some Canadian engineers may fall further behind in this race to become lean. The gap will continue to widen between an ever-growing need for lean education and Canada’s ability to fill it. Canadian universities must respond to this need in an effort to create well-rounded engineers and to sustain the Canadian economy and standard of living.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,028 | 0,011 |
| Communication savante | 0,015 | 0,006 |
| Science ouverte | 0,003 | 0,008 |
| Intégrité de la recherche | 0,006 | 0,013 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,088 | 0,025 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».