Notice bibliographique
Résumé
The high level of construction activity in the Alberta pipeline projects leads to significant concerns about cost, schedule, safety, engineering productivity, and construction productivity in regards to pipeline operations and activities. Moreover, the growth of industry in Canada and specifically in Alberta means that more products are being processed today than ever before. Those products must be transmitted effectively to the desired area. However, pipeline projects, due to their characteristics and nature, are categorized differently than heavy industrial projects. These characteristics include the length of the pipes in addition to the vast area they cover and also different regulatory processes that pipeline projects follow in order to obtain necessary construction permits. These characteristics are different than other typical industrial projects. Comparatively, the time and work required through the front end-planning phase of pipeline projects sharply increase due to this fact that pipelines vary in lengths and the products they carried inside. Pipelines need a huge amount of study and design prior to the detailed engineering and construction phases. Moreover, the sensitivity of these projects requires special consideration. Several pipeline projects have been either delayed or stopped due to environmental impact concerns, hazardous risks, and public resistance. These specific characteristics, impact factors, and environmental risks create a pressing need for benchmarking of these projects. Benchmarking is a reliable comparison tool used to compare one project's data against other companies’ and operators’ data in the industry. A benchmarking system has been developed over the past several years as a collaboration work between COAA (Construction Owners Association of Alberta) and CII (Construction Industry Institute) to assess the performance of Alberta pipeline projects. An analysis of a research’s results indicated areas for enhancements. The purpose of the current research project is to expand and extend the previous benchmarking system, focusing on activities and methods utilized by engineering, procurement, and construction (EPC) owners and contractors to design and build the pipeline projects. The results of previous Alberta pipeline projects report indicate that specific metrics for pipeline projects need to be better defined and developed in order to build a new, valuable performance assessment system. These new metrics and performance assessment techniques will span the project life cycle from front end planning and detailed engineering through construction, commissioning, and start-up. The current areas for heavy industrial metrics, such as cost, schedule, safety, rework, and productivity will be the focus in developing these new metrics for pipeline projects. This research project contains an extensive literature review of pipeline construction specifically in Alberta in addition to the history and current practices of benchmarking. The data collection phase of the research includes two sets of interview and survey conducted among pipeline industry experts. Finally, conclusions and recommendations achieved from the analyses of gathered information are presented.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».