Relevant bibliographies by topics / Classification of inventory

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Classification of inventory'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 February 2022

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Journal articles on the topic "Classification of inventory"

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Ly, Rathanaksambath, and Morrakot Raweewan. "Flexible ABC Inventory Classification." KnE Life Sciences 4, no. 2 (March 1, 2018): 228. http://dx.doi.org/10.18502/kls.v4i2.1676.

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ABC inventory classification is a well-known approach to assign inventory item into A, B, and C groups based on their sales and usage volume. This helps inventory management become more efficient. Behind its advantage, it usually shows some problems with an inventory budget and warehouse space because the ABC assignment of SKUs are mad e without an inventory budget and space available involved. In this paper, the ABC group under restricted of an inventory budget and warehouse space to maximize the profit with optimal service level is presented. We establish this proposed model to enhance the existing ABC approach to be more applicable in real life, which has the limited inventory budget and warehouse space. Keywords: ABC Inventory Classification; Inventory Management
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May, Benjamin Isaac, Michael P. Atkinson, and Geraldo Ferrer. "Applying inventory classification to a large inventory management system." Journal of Operations and Supply Chain Management 10, no. 1 (June 28, 2017): 68. http://dx.doi.org/10.12660/joscmv10n1p68-86.

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Dhoka, Dinesh Kumar. "“XYZ” Inventory Classification & Challenges." IOSR Journal of Economics and Finance 2, no. 2 (2013): 23–26. http://dx.doi.org/10.9790/5933-0222326.

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Dhoka, Dinesh. "ABC Classification for Inventory Optimization." IOSR Journal of Business and Management 15, no. 1 (2013): 38–41. http://dx.doi.org/10.9790/487x-1513841.

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JESNESS, CARL F. "The Jesness Inventory Classification System." Criminal Justice and Behavior 15, no. 1 (March 1988): 78–91. http://dx.doi.org/10.1177/0093854888015001007.

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The Jesness Inventory Classification System is a simple, objective method for classifying offenders into one of nine subtypes. Having its origin in the I-level classification, the JI system has gone through a long evolution. The procedure for classification now requires only the responses to the 155-item Jesness Inventory, which can be hand-scored. Studies with both delinquents and nondelinquents have shown the classification to be comprehensive and valid.
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Flores, Benito E., David L. Olson, and V. K. Dorai. "Management of multicriteria inventory classification." Mathematical and Computer Modelling 16, no. 12 (December 1992): 71–82. http://dx.doi.org/10.1016/0895-7177(92)90021-c.

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Van Zandt, CDR Robert A., and Jorice Williams. "RESPONSE RESOURCE INVENTORY." International Oil Spill Conference Proceedings 1997, no. 1 (April 1, 1997): 909–10. http://dx.doi.org/10.7901/2169-3358-1997-1-909.

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ABSTRACT The Oil Pollution Act of 1990 mandated the creation of a national database of response resources. This has been accomplished with the creation of the Response Resource Inventory (RRI) located and maintained at the National Strike Force Coordination Center in Elizabeth City, North Carolina. Recent revisions to the Oil Spill Removal Organization (OSRO) classification program have mandated the use of the RRI by OSRO applicants. This poster session will describe how data are obtained from OSRO applicants, how they are manipulated to determine the OSRO's classifications, and how plan holders can access and use the RRI as a tool to conduct their own analysis of an OSRO's capacity to meet their specific planning requirements.
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Taminskas, Julius, Marijus Pileckas, Rasa Šimanauskienė, and Rita Linkevičienė. "Wetland classification and inventory in Lithuania." Baltica 25, no. 1 (June 12, 2012): 33–44. http://dx.doi.org/10.5200/baltica.2012.25.03.

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Massmann, Melina, Maurice Meyer, Maximilian Frank, Sebastian von Enzberg, Arno Kühn, and Roman Dumitrescu. "Method for data inventory and classification." Procedia CIRP 93 (2020): 234–39. http://dx.doi.org/10.1016/j.procir.2020.04.033.

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Finlayson, C. M., and A. G. Valk. "Wetland classification and inventory: A summary." Vegetatio 118, no. 1-2 (June 1995): 185–92. http://dx.doi.org/10.1007/bf00045199.

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Dissertations / Theses on the topic "Classification of inventory"

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THOME, ANTONIO MARCIO TAVARES. "CLASSIFICATION AND INVENTORY MANAGEMENT OF RETAIL PRODUCTS: A CASE STUDY." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2009. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=14320@1.

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Estoques ocupam um lugar central na economia e nas empresas contemporâneas. Novos paradigmas surgem na gestão de estoques, cada vez mais percebidos como elemento estratégico para a criação de valor na cadeia de suprimento. Estoques passaram a constituir um elemento chave na busca constante por vantagens competitivas entre empresas. Esta dissertação revê os principais conceitos e definições de estoques de produtos acabados. Modelos, heurísticas e políticas de estoques aplicadas a sistemas de distribuição de produtos de varejo envolvendo vários produtos, Um almoxarifado e N revendedores, são definidos. Métodos de agrupamento de itens em classes ABC homogêneas são revistos e ilustrados com aplicações numéricas a produtos do ramo farmacêutico. São definidos os principais modelos e políticas de gestão de estoques adequados às diferentes classes de produtos do estudo de caso. A lógica de ressuprimentos coordenados de produtos de varejo em cadeias de suprimento de elos múltiplos é apresentada com a ajuda de exemplos. Finalmente, políticas alternativas de estoques para diferentes classes de produtos em sistemas de distribuição divergentes são apresentadas. Aspectos práticos ligados à implantação de modelos matemáticos e políticas de estoques em redes de varejo são enfatizados na conclusão do trabalho.
Inventories are a central piece in contemporary economies and businesses. New paradigms appear in the area of inventory management, which is being increasingly perceived as a strategic element for value creation in supply chains. Inventories became a key element in the constant search for competitive advantages among companies. This dissertation reviews the main concepts and definitions of inventories as applied to finished products. Inventory models, heuristics and policies for distribution systems of retail products involving several products, One-warehouse and N retailers, are defined. Methods designed to regroup items in ABC classes are reviewed and illustrated by numerical applications to pharmaceutical products. The main models and inventory control policies adapted to different classes of products from the case study are defined. The logic of coordinated resupply of retail products in multi-echelon supply chains is presented with examples. Finally, alternative inventory policies for different classes of products in divergent distribution systems are presented. Practical aspects related to the implementation of mathematical models and policies in retail supply chains are emphasized in the conclusion of this work.
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Zowid, Fauzi Mohammed. "Development and performance evaluation of multi-criteria inventory classification methods." Thesis, Bordeaux, 2020. http://www.theses.fr/2020BORD0331.

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Cette thèse traite du problème de la classification des produits dans les systèmes de gestion de stock. Plus précisément, elle vise à proposer de nouvelles méthodes de classification pour résoudre le problème de la classification multicritères des produits en stock (MCIC). Actuellement, la méthode ABC de classification des produits en stock est largement utilisée pour rationaliser les systèmes de gestion de stock composés de milliers de produits (SKU). Les méthodes de classification des stocks ABC à un seul critère sont souvent utilisées dans la pratique et, récemment, les MCIC ont également attiré l’attention des chercheurs et des industriels. En ce qui concerne les méthodes multicritères MCIC, un grand nombre de méthodes ont été développées dans la littérature, appartenant à trois approches principales, à savoir: (1) l'approche à base de Machine Learning (ML), (2) programmation mathématique (MP), et (3) multicritères d’aide à la décision (MCDM). Dans ML, de nombreuses méthodes de type ML supervisé ont été proposées ainsi qu'un certain nombre de méthodes hybrides. Cependant, à notre connaissance, très peu d'études de recherche ont envisagé le type ML non supervisé. Concernant les approches de type MP, un certain nombre de méthodes ont été développées en utilisant la programmation linéaire et non linéaire, telles que les méthodes Ng et ZF. Cependant, la plupart de ces méthodes doivent encore être améliorées pour en limiter les inconvénients. Sur MCDM, plusieurs méthodes ont été proposées pour fournir des classifications ABC, y compris la méthode TOPSIS (technique for order preference by similarity to ideal solution), qui est bien connue pour son attractivité et son utilisation, ainsi que certaines méthodes hybrides combinées avec TOPSIS. Il convient de noter que la plupart des études publiées se sont uniquement concentrées sur la proposition de méthodes de classification pour classer les SKUs dans un système de gestion de stock avec un intérêt limité par rapport à l'objectif initial et le plus important de notre travail, qui est la performance en termes de coûts et de niveau de service de la méthode proposée. De plus, la plupart des études existantes n'ont pas considéré des systèmes de gestion de stock avec un grand nombre de données réelles (un grand nombre de références) pour évaluer empiriquement leurs performances et recommander l'utilisation d’une méthode particulière pour des mises en pratique réelles. Ainsi, cette thèse propose d'abord d'évaluer la performance (coût et service) des méthodes MCIC existantes et de proposer diverses méthodes de classification alternatives qui réduisent les coûts et conduisent à des niveaux de service plus élevés. Plus précisément, trois méthodes de type ML non supervisées sont proposées et analysées : Agglomerative hierarchical clustering, Gaussian mixture model et K-means. En outre, d'autres méthodes hybrides dans les approches de type MP et MCDM sont également développées. Ces méthodes proposées représentent une hybridation des méthodes TOPSIS et Ng avec la méthode Triangular distribution, la méthode Simple additive weighting (SAW) et la méthode Multi-Objective Optimization Method by Ratio Analysis (MOORA). Pour mener nos recherches, la thèse analyse empiriquement les performances des méthodes considérées au moyen de deux jeux de données. Le premier jeu de données est un jeu de données benchmark qui provient d’une unité d’hôpital, souvent utilisé dans la littérature traitant des méthodes MCIC, composé de 47 SKUs. Le deuxième jeu de données se compose de 9086 SKUs et provient d'un détaillant aux Pays-Bas qui vend des produits de bricolage. Les performances des méthodes proposées sont comparées à celles des méthodes de classification MCIC existantes dans la littérature. Les résultats empiriques révèlent que les méthodes proposées donnent des performances prometteuses en conduisant à une plus grande efficacité combinée service-coût, notamment pour le second jeu de données très significatif
This thesis deals with the issue of inventory classification within supply chains. More specifically, it aims to provide new alternative classification methods to address the multi-criteria inventory classification (MCIC) problem. It is well known that the ABC inventory classification technique is widely used to streamline inventory systems composed of thousands of stock-keeping-units (SKUs). Single-criterion inventory classification (SCIC) methods are often used in practice and recently MCIC techniques have also attracted researchers and practitioners. With regard to the MCIC techniques, large number of studies have been developed that belong to three main approaches, namely: (1) the machine learning (ML), (2) the mathematical programming (MP), and (3) the multi-criteria decision making (MCDM). On the ML approach, many research methods belonging to the supervised ML type have been proposed as well as a number of hybrid methods. However, to the best of our knowledge, very few research studies have considered the unsupervised ML type. On the MP approach, a number of methods have been developed using linear and non-linear programming, such as the Ng and the ZF methods. Yet, most of these developed methods still can be granted more attentions for more improvements and shortcomings reduction. On the MCDM approach, several methods have been proposed to provide ABC classifications, including the TOPSIS (technique for order preference by similarity to ideal solution) method, which is well known for its wide attractiveness and utilization, as well as some hybrid TOPSIS methods.It is worth noting that most of the published studies have only focused on providing classification methods to rank the SKUs in an inventory system without any interest in the original and most important goal of this exercise, which is achieving a combined service-cost inventory performance, i.e. the maximization of service levels and the minimization of inventory costs. Moreover, most of the existing studies have not considered large and real-life datasets to recommend the run of MCIC technique for real life implementations. Thus, this thesis proposes first to evaluate the inventory performance (cost and service) of existing MCIC methods and to provide various alternative classification methods that lead to higher service and cost performance. More specifically, three unsupervised machine learning methods are proposed and analyzed: the Agglomerative hierarchical clustering, the Gaussian mixture model and K-means. In addition, other hybrid methods within the MP and MCDM approaches are also developed. These proposed methods represent a hybridization of the TOPSIS and Ng methods with the triangular distribution, the Simple additive weighting (SAW) and the Multi-objective optimization method by ratio analysis (MOORA).To conduct our research, the thesis empirically analyzes the performance of the proposed methods by means of two datasets containing more than nine thousand SKUs. The first dataset is a benchmark dataset originating from a Hospital Respiratory Theory Unit, often used in the literature dealing with the MCIC methods, composed of 47 SKUs. The second dataset consists of 9,086 SKUs and coming from a retailer in the Netherlands. The performances of the proposed methods are compared to that of existing MCIC classification methods in the literature. The empirical results reveal that the proposed methods can carry promising performances by leading to a higher combined service-cost efficiency
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Al-Qatawneh, Lina Khalil. "A study of inventory classification in healthcare logistics using system dynamics modelling." Thesis, Sheffield Hallam University, 2006. http://shura.shu.ac.uk/19256/.

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One of the key challenges for a modern day health care provider is to dispense high quality of medical care while limiting or even reducing the health care expenditures. This research work endeavours to meet this challenge through effective management of hospitals logistics systems. The aim of this research work is to provide a structured mechanism for modelling and analysing health care logistics to be able to understand its dynamic behaviour and effectively manage its logistical activities on the basis of the model. In order to achieve the research objectives, this research uses system dynamics as the main medium of analysis, and in particular, employs an integrated system dynamics framework which has been used previously for manufacturing industry supply chain designs and tests the feasibility of the framework for analysing and modelling health care logistics. This is ascertained by developing and incorporating a decision making metrics in the system dynamics model based on item criticality, usage, and value to optimise overall logistics costs. System Dynamics methodology is employed at first to develop a model for existing inventory control decisions, and subsequently to produce two alternative approaches based on traditional (R, s, S) inventory control approach and Continuous Replenishment Inventory and Order Based Production Control CR(IOBPCS) approach. These approaches are tested for two case hospitals, namely: Children's National Medical Center (CNMC) USA, and Derbyshire Royal Infirmary (DRI) UK. The dynamic analysis for each case revealed problems in terms of multistage inventories and order batching, which could lead to demand amplification causing a detrimental effect on the inventory management throughout the supply chain. Accordingly, the simulations results produced for the two cases are benchmarked using alternative strategies in terms of lower inventory cost, and robustness to meet the unpredictable demand arising from a large number of items. Overall, this research work has enhanced the understanding of hospitals logistics systems by building qualitative and quantitative models. More specifically, this research work has illustrated the applicability of the integrated system dynamics framework in analysing and modelling hospitals logistics systems and inventory control decisions. One particular contribution of this study is introducing inventory classification based on the criticality of items for patient needs which is more suited for health care situations rather purely cost based policies prevalent in other manufacturing and service chains. Therefore, this work has rigorously tested a multi-criteria based inventory classification method that takes into account the criticality of use, cost, and usage value of items for optimising overall inventory cost while maintaining the required patient care/service level. Future studies may be conducted to further evaluate the trade-offs in between different logistics decision making (such as, inventory control, service level, purchasing, transportation and warehousing) in order to design a set of "best practice" simulation models to optimise the overall dynamic behaviour for health care supply chains.
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Maudie, Alan John. "Forest inventory classification using aerial image texture in the New Brunswick Acadian forest region." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0017/MQ48024.pdf.

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Sandy, Alexis Emily. "Environmental and Digital Data Analysis of the National Wetlands Inventory (NWI) Landscape Position Classification System." Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/33572.

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The National Wetlands Inventory (NWI) is the definitive source for wetland resources in the United States. The NWI production unit in Hadley, MA has begun to upgrade their digital map database, integrating descriptors for assessment of wetland functions. Updating is conducted manually and some automation is needed to increase production and efficiency. This study assigned landscape position descriptor codes to NWI wetland polygons and correlated polygon environmental properties with public domain terrain, soils, hydrology, and vegetation data within the Coastal Plain of Virginia. Environmental properties were applied to a non-metric multidimensional scaling technique to identify similarities within individual landscape positions based on wetland plant indicators, primary and secondary hydrology indicators, and field indicators of hydric soils. Individual NWI landscape position classes were linked to field-validated environmental properties. Measures provided by this analysis indicated that wetland plant occurrence and wetland plant status obtained a stress value of 0.136 (Kruskalâ s stress measure = poor), which is a poor indicator when determining correlation among wetland environmental properties. This is due principally to the highly-variable plant distribution and wetland plant status found among the field-validated sites. Primary and secondary hydrology indicators obtained a stress rating of 0.097 (Kruskalâ s stress measure = good) for correlation. The hydrology indicators measured in this analysis had a high level of correlation with all NWI landscape position classes due the common occurrence of at least one primary hydrology indicator in all field validated wetlands. The secondary indicators had an increased accuracy in landscape position discrimination over the primary indicators because they were less ubiquitous. Hydric soil characteristics listed in the 1987 Manual and NTCHS field indicators of hydric soils proved to be a relatively poor indicator, based on Kruskalâ s stress measure of 0.117, for contrasting landscape position classes because the same values occurred across all classes. The six NWI fieldâ validated landscape position classes used in this study were then further applied in a public domain digital data analysis. Mean pixel attribute values extracted from the 180 field-validated wetlands were analyzed using cluster analysis. The percent hydric soil component displayed the greatest variance when compared to elevation and slope curvature, streamflow and waterbody, Cowardin classification, and wetland vegetation type. Limitations of the soil survey data included: variable date of acquisition, small scale compared to wetland size, and variable quality. Flow had limitations related to its linear attributes, therefore is often found insignificant when evaluating pixel values that are mean of selected pixels across of wetland landscape position polygons. NLCD data limitations included poor quality resolution (large pixel size) and variable classification of cover types. The three sources of information that would improve wetland mapping and modeling the subtle changes in elevation and slope curvature that characterize wetland landscapes are: recent high resolution leaf-off aerial photography, high-quality soil survey data, and high-resolution elevation data. Due to the data limitations and the choice of variables used in this study, development of models and rules that clearly separate the six different landscape positions was not possible, and thus automation of coding could not be attempted.
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Isiaka, Adeiza Lasisi. "Ebira English in Nigerian Supersystems: Inventory and Variation." Doctoral thesis, Universitätsbibliothek Chemnitz, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-225496.

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Die vorliegende Arbeit mit dem Titel „Ebíra English in Nigerian Supersystems: Inventory and Variation“ befasst sich mit einer kleinen Varietät des Nigerianischen Englisch, die für eine Untersuchung aus zwei Gründen besonders geeignet erscheint: Einerseits bin ich selbst Mitglied dieser Volksgruppe, was mir einen besonderen Zugang zu guten, aktuellen und vor allem natürlichen Sprachdaten ermöglicht. Diese sind für eine soziophonetische Untersuchung mit den Konzepten und modernen Methoden der Variationslinguistik von besonderer Bedeutung. Andererseits ist die vorliegende Arbeit keine weitere Studie über die großen Systeme des nigerianischen Englisch oder über die beiden größten und bereits relativ gut untersuchten Systeme des Yoruba-Englisch im Südwesten des Landes oder des Hausa-Englisch im Norden, sondern über eine relative kleine Gruppe dazwischen, die historisch zunächst von den Yoruba und später immer mehr von den Hausa-Sprechern beeinflusst wurde und nach wie vor beeinflusst ist. Diese empirische soziophonetische Studie stellt zwei Forschungsfragen: FF1) Welches Vokalinventar besitzt Ebíra Englisch? Diese Frage ergibt sich aus den widersprüchlichen Ergebnissen vorheriger Untersuchungen (zu Nigerianischen, Yoruba- bzw. Hausa-Englisch) und soll hier erstmals in einer Analyse von digitalen Aufnahmen von 28 jüngeren und älteren Männern und Frauen (16 bzw. 12) aus den Jahren 2014-2016 untersucht werden. Diese Aufnahmen wurden im Rahmen von soziolinguistischen Interviews gemacht, die die bekannten Sprachstile (nach Labov) umfassen: Wortliste, Lesepassage (die bewährte Kurzgeschichte The Boy who Cried Wolf mit jeweils 90 vorkommenden englischen Vokalen) und Konversation. Diese Frage ist auch vor dem Hintergrund des Einflusses der beiden nahen Hauptvarietäten Yoruba- und Hausa-Englisch interessant (FF1b). Auf der Grundlage von fast 15.000 extrahierten Vokalen erfolgte jeweils nach der sorgfältigen Aussortierung unbrauchbarer oder unvollständiger Daten eine quantitative Untersuchung mit Hilfe des Analyseinstruments PRAAT, mit dem sich die Vokalqualität in Form von Formanten messen und darstellen lässt. Die Untersuchung umfasste die bekannten Monophthongkontraste (nach Wells` lexical sets) FLEECE & KIT, FOOT & GOOSE (+ USE ), LOT & THOUGHT & STRUT , TRAP & BATH & lettER , sowie NURSE , und die relativen Diphthonge FACE , GOAT und CURE. FF2) Welche sprachlichen und sozialen Variablen können die Variation dieses Ebíra Englisch Vokalsystems erklären? Neben den bekannten sozialen Variablen Alter (bzw. Altersgruppe), Geschlecht, Mehrsprachigkeit und Bildung wurden v.a. die sprachlichen Variablen Vokaldauer, phonetische Umgebung der Vokale und Sprachstil untersucht. Interessanterweise war für eine so detaillierte Analyse der Variation die zunächst recht groß wirkende Anzahl der extrahierten Vokale nicht in jedem Fall groß genug oder nicht gut genug verteilt.
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Castro, Villagón Lizza, and Caleb Rangel. "Determining Supply Chain Inventory Locations Through Product Classification : A Case Study of a Sealing Material Company." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Centre of Logistics and Supply Chain Management, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-18426.

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Nowadays firms must develop inventory policies that enable them to cope with the changing marketplace. Determining proper inventory locations can help decrease costs related to inventory holding and transportation. Moreover, this allows firms to respond in a timely manner to customers’ requirements. As a result profit margins can be enhanced as well as the competitiveness of a firm. However, the decision of where to locate inventory in a supply chain is difficult since many companies are managed independently. The present research is developed as a case study where product classification, customer and supplier segmentation schemes are reviewed in order to determine appropriate inventory locations along the supply chain. The thesis is written upon literature and empirical research, where most of the data was collected through personal interviews and observations at the supply chain management offices of a distributor for sealing material parts in Europe. Our conclusion shows that product classification has an important impact on inventory location decisions. Also, we conclude that products should be classified based on both physical characteristics and demand factors, as well as according to customers’ requirements. Another factor to be considered when deciding on inventory location is supply risks, due to issues related to raw material availability and capacity. Nonetheless, the selection of classification variables is challenging as it is hard to determine which factors are more relevant than others as this varies depending on each firms’ needs. In addition, we find that supply chain strategies are not realistic due to the constant changes in the business environment and the inability of a firm to manage whole supply chains. Furthermore, a high level of communication among supply chain partners is fundamental, especially when a centralized inventory policy and a postponement strategy are in place.
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Book, Oscar, Isac Falkenberg, and Oscar Gunnarsson. "Orsaker till saldodifferenser inom fordonsindustrin." Thesis, Malmö universitet, Fakulteten för kultur och samhälle (KS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-24023.

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Den här uppsatsens syfte var att analysera saldodifferenser på Haldex. För att besvara detta syfte genomfördes en kvalitativ metod i form av intervjuer, observationer samt en enkät. Detta empiriska material analyserades sedan med hjälp av relevanta teorier som berörde inventory management, RFID teknik och anställdas beteende. Det vi kom fram till var att saldodifferenserna på Haldex beror på både mänskliga och teknologiska fel. De mänskliga felen beror på en bristande utbildning i det nya affärssystemet som implementerades för drygt ett år sedan. De teknologiska felen beror på svaga kriterier vid klassificering av sitt lager. Idag använder sig Haldex av ett det vanligaste kriteriet vid en ABC klassificering, nämligen värdet på produkten. Vi föreslår att det bör kompletteras med ledtiden och betydelsen av produkten för att ge ett mer rättvisande klassificering på lagret. För att minska felen som uppstår i lagret föreslår vi att Haldex bör implementera RFID teknologin på sina A produkter.
The purpose of this study was to analyze inventory inaccuracy at Haldex. In order to answer the purpose a qualitative method in the form of interviews, a survey and observations were conducted. The empirical material was then later analyzed with relevant theories regarding inventory inaccuracy. This study found that the inventory inaccuracy at Haldex mainly was a result of human errors combined with technological errors. The human errors came from a lack of knowledge in the company's ERP system AX12. The interviews found that the system had been implemented too fast and without relevant training, which later resulted in employees not knowing how to properly use it. The technological errors came from the company's weak criteria’s when it came to classify the inventory. Today Haldex uses an ABC-classification that is based on the products value, this essay suggests that lead time and importance of the product should be added. In order to minimize inventory errors this essay suggest that RFID technology needs to be added to the company's A-products.
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Kučerová, Kamila. "Návrh na zlepšení řízení zásob." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2016. http://www.nusl.cz/ntk/nusl-234863.

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The thesis is focused on the study and optimize inventory management at Kordárna Plus, a. s. The theoretical part describes the characteristics of the basic concepts related to inventory management, classification, costs associated there with and methods of inventory control. The practical part is focused on the analysis of stocks on the process of procuring, warehousing and inventory control. This analysis uncovered deficiencies for which they proposed solutions. Proposals should lead to improved inventory management in the company.
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Jensen, Jana D. "STUDENTS’ UNDERSTANDINGS OF ACID-BASE REACTIONS INVESTIGATED THROUGH THEIR CLASSIFICATION SCHEMES AND THE ACID-BASE REACTIONS CONCEPT INVENTORY." Miami University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=miami1365611297.

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Books on the topic "Classification of inventory"

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Gottfredson, Gary D. Position classification inventory (PCI): Professional manual. Odessa, Fla: Psychological Assessment Resources, 1991.

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Thapa, V. K. An inventory of Nepal's insects. Kathmandu: IUCN-The World Conservation Union, 1997.

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Baltazar, Clare R. An inventory of Philippine insects. Laguna, Philippines: University of the Philippines Los Baños, University Publications Office, 1990.

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Korb, Roslyn A. Postsecondary education facilities inventory and classification manual. [Washington, D.C.]: U.S. Dept. of Education, Office of Educational Research and Improvement, National Center for Education Statistics, 1992.

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Finlayson, C. Max, and A. G. van der Valk, eds. Classification and Inventory of the World’s Wetlands. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0427-2.

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Cyros, Kreon L. Postsecondary Education Facilities Inventory and Classification Manual (FICM). 2nd ed. Washington, D.C.]: The Institute, 2006.

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Inventory classification innovation: Paving the way for electronic commerce and vendor managed inventory. Boca Raton: St. Lucie Press, 1999.

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New Zealand inventory of biodiversity. Christchurch, N.Z: Canterbury University Press, 2009.

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McCain, Michael E. Stream habitat classification and inventory procedures for northern California. Eureka, CA?]: U.S. Dept. of Agriculture, Forest Service, Pacific Southwest Region, 1990.

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Ihilevich, David. Defense mechanisms: Their classification, correlates, and measurement with the defense mechanisms inventory. Odessa, Fla: Psychological Assessment Resources, 1993.

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Book chapters on the topic "Classification of inventory"

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Finlayson, C. M., and A. G. van der Valk. "Wetland classification and inventory: A summary." In Classification and Inventory of the World’s Wetlands, 185–92. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0427-2_15.

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Gopal, B., and M. Sah. "Inventory and classification of wetlands in India." In Classification and Inventory of the World’s Wetlands, 39–48. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0427-2_5.

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Zoltai, S. C., and D. H. Vitt. "Canadian wetlands: Environmental gradients and classification." In Classification and Inventory of the World’s Wetlands, 131–37. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0427-2_11.

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Lu, J. "Ecological significance and classification of Chinese wetlands." In Classification and Inventory of the World’s Wetlands, 49–56. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0427-2_6.

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Scott, D. A., and T. A. Jones. "Classification and inventory of wetlands: A global overview." In Classification and Inventory of the World’s Wetlands, 3–16. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0427-2_2.

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Finlayson, C. Max, and A. G. van der Valk. "Editorial." In Classification and Inventory of the World’s Wetlands, 1–2. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0427-2_1.

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Naranjo, L. G. "An evaluation of the first inventory of South American wetlands." In Classification and Inventory of the World’s Wetlands, 125–29. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0427-2_10.

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Cowardin, Lewis M., and Francis C. Golet. "US Fish and Wildlife Service 1979 wetland classification: A review." In Classification and Inventory of the World’s Wetlands, 139–52. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0427-2_12.

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Wilen, B. O., and M. K. Bates. "The US Fish and Wildlife Service’s National Wetlands Inventory Project." In Classification and Inventory of the World’s Wetlands, 153–69. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0427-2_13.

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Novitzki, R. P. "EMAP-Wetlands: A sampling design with global application." In Classification and Inventory of the World’s Wetlands, 171–84. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0427-2_14.

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Conference papers on the topic "Classification of inventory"

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Xue, Dongjuan. "Inventory classification tree model based on inventory Classification policy in Manufacturing Enterprises." In 2015 6th International Conference on Manufacturing Science and Engineering. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/icmse-15.2015.171.

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Deb, Mahuya, Prabjot Kaur, Kandarpa Kumar Sarma, and Nikos Mastorakis. "Inventory Classification Using Fuzzy Approach." In 2018 5th International Conference on Mathematics and Computers in Sciences and Industry (MCSI). IEEE, 2018. http://dx.doi.org/10.1109/mcsi.2018.00033.

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Innar Liiv. "Inventory classification enhancement with demand associations." In 2006 IEEE International Conference on Service Operations and Logistics, and Informatics. IEEE, 2006. http://dx.doi.org/10.1109/soli.2006.234903.

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Liiv, Innar. "Inventory classification enhancement with demand associations." In 2006 IEEE International Conference on Service Operations and Logistics, and Informatics. IEEE, 2006. http://dx.doi.org/10.1109/soli.2006.328975.

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Ye, Weilong. "ABC Inventory Classification Based on Multicriteria Optimization." In First International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40932(246)667.

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Zhenyu, Liu, Wu Jun, and Yan Zhenying. "Application of Association Rules Mining in Inventory Classification." In 2009 Second International Workshop on Computer Science and Engineering. IEEE, 2009. http://dx.doi.org/10.1109/wcse.2009.884.

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Lajili, Imen, Talel Ladhari, and M. Zied Babai. "Multi-criteria inventory classification problem: A consensus approach." In 2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO 2013). IEEE, 2013. http://dx.doi.org/10.1109/icmsao.2013.6552687.

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Wang, F., H. Y. Ng, and T. E. Ng. "Novel SKU Classification Approach for Autonomous Inventory Planning." In 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2018. http://dx.doi.org/10.1109/ieem.2018.8607736.

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Liiv, Innar. "Visualization and data mining method for inventory classification." In 2007 IEEE International Conference on Service Operations and Logistics, and Informatics. IEEE, 2007. http://dx.doi.org/10.1109/soli.2007.4383909.

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Saksena, Aman Kumar, and Reshu Agarwal. "Methods for Classification of Items for Inventory Management." In 2021 International Conference on Computer Communication and Informatics (ICCCI). IEEE, 2021. http://dx.doi.org/10.1109/iccci50826.2021.9402588.

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Reports on the topic "Classification of inventory"

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May, Dennis M., John S. Vissage, and D. Vince Few. New Tree-Classification System Used by the Southern Forest Inventory and Analysis Unit. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station, 1990. http://dx.doi.org/10.2737/so-gtr-076.

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May, Dennis M., John S. Vissage, and D. Vince Few. New Tree-Classification System Used by the Southern Forest Inventory and Analysis Unit. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station, 1990. http://dx.doi.org/10.2737/so-gtr-76.

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Wells, Aaron, Tracy Christopherson, Gerald Frost, Matthew Macander, Susan Ives, Robert McNown, and Erin Johnson. Ecological land survey and soils inventory for Katmai National Park and Preserve, 2016–2017. National Park Service, September 2021. http://dx.doi.org/10.36967/nrr-2287466.

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This study was conducted to inventory, classify, and map soils and vegetation within the ecosystems of Katmai National Park and Preserve (KATM) using an ecological land survey (ELS) approach. The ecosystem classes identified in the ELS effort were mapped across the park, using an archive of Geo-graphic Information System (GIS) and Remote Sensing (RS) datasets pertaining to land cover, topography, surficial geology, and glacial history. The description and mapping of the landform-vegetation-soil relationships identified in the ELS work provides tools to support the design and implementation of future field- and RS-based studies, facilitates further analysis and contextualization of existing data, and will help inform natural resource management decisions. We collected information on the geomorphic, topographic, hydrologic, pedologic, and vegetation characteristics of ecosystems using a dataset of 724 field plots, of which 407 were sampled by ABR, Inc.—Environmental Research and Services (ABR) staff in 2016–2017, and 317 were from existing, ancillary datasets. ABR field plots were located along transects that were selected using a gradient-direct sampling scheme (Austin and Heligers 1989) to collect data for the range of ecological conditions present within KATM, and to provide the data needed to interpret ecosystem and soils development. The field plot dataset encompassed all of the major environmental gradients and landscape histories present in KATM. Individual state-factors (e.g., soil pH, slope aspect) and other ecosystem components (e.g., geomorphic unit, vegetation species composition and structure) were measured or categorized using standard classification systems developed for Alaska. We described and analyzed the hierarchical relationships among the ecosystem components to classify 92 Plot Ecotypes (local-scale ecosystems) that best partitioned the variation in soils, vegetation, and disturbance properties observed at the field plots. From the 92 Plot Ecotypes, we developed classifications of Map Ecotypes and Disturbance Landscapes that could be mapped across the park. Additionally, using an existing surficial geology map for KATM, we developed a map of Generalized Soil Texture by aggregating similar surficial geology classes into a reduced set of classes representing the predominant soil textures in each. We then intersected the Ecotype map with the General-ized Soil Texture Map in a GIS and aggregated combinations of Map Ecotypes with similar soils to derive and map Soil Landscapes and Soil Great Groups. The classification of Great Groups captures information on the soil as a whole, as opposed to the subgroup classification which focuses on the properties of specific horizons (Soil Survey Staff 1999). Of the 724 plots included in the Ecotype analysis, sufficient soils data for classifying soil subgroups was available for 467 plots. Soils from 8 orders of soil taxonomy were encountered during the field sampling: Alfisols (<1% of the mapped area), Andisols (3%), Entisols (45%), Gelisols (<1%), Histosols (12%), Inceptisols (22%), Mollisols (<1%), and Spodosols (16%). Within these 8 Soil Orders, field plots corresponded to a total of 74 Soil Subgroups, the most common of which were Typic Cryaquents, Typic Cryorthents, Histic Cryaquepts, Vitrandic Cryorthents, and Typic Cryofluvents.
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Henderson, Tim, Vincent Santucci, Tim Connors, and Justin Tweet. National Park Service geologic type section inventory: Klamath Inventory & Monitoring Network. National Park Service, July 2021. http://dx.doi.org/10.36967/nrr-2286915.

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A fundamental responsibility of the National Park Service (NPS) is to ensure that park resources are preserved, protected, and managed in consideration of the resources themselves and for the benefit and enjoyment by the public. Through the inventory, monitoring, and study of park resources, we gain a greater understanding of the scope, significance, distribution, and management issues associated with these resources and their use. This baseline of natural resource information is available to inform park managers, scientists, stakeholders, and the public about the conditions of these resources and the factors or activities which may threaten or influence their stability. There are several different categories of geologic or stratigraphic units (supergroup, group, formation, member, bed) which represent a hierarchical system of classification. The mapping of stratigraphic units involves the evaluation of lithologies, bedding properties, thickness, geographic distribution, and other factors. If a new mappable geologic unit is identified, it may be described and named through a rigorously defined process that is standardized and codified by the professional geologic community (North American Commission on Stratigraphic Nomenclature 2005). In most instances when a new geologic unit such as a formation is described and named in the scientific literature, a specific and well-exposed section of the unit is designated as the type section or type locality (see Definitions). The type section is an important reference section for a named geologic unit which presents a relatively complete and representative profile. The type or reference section is important both historically and scientifically, and should be protected and conserved for researchers to study and evaluate in the future. Therefore, this inventory of geologic type sections in NPS areas is an important effort in documenting these locations in order that NPS staff recognize and protect these areas for future studies. The documentation of all geologic type sections throughout the 423 units of the NPS is an ambitious undertaking. The strategy for this project is to select a subset of parks to begin research for the occurrence of geologic type sections within particular parks. The focus adopted for completing the baseline inventories throughout the NPS was centered on the 32 inventory and monitoring networks (I&M) established during the late 1990s. The I&M networks are clusters of parks within a defined geographic area based on the ecoregions of North America (Fenneman 1946; Bailey 1976; Omernik 1987). These networks share similar physical resources (geology, hydrology, climate), biological resources (flora, fauna), and ecological characteristics. Specialists familiar with the resources and ecological parameters of the network, and associated parks, work with park staff to support network level activities (inventory, monitoring, research, data management). Adopting a network-based approach to inventories worked well when the NPS undertook paleontological resource inventories for the 32 I&M networks. The network approach is also being applied to the inventory for the geologic type sections in the NPS. The planning team from the NPS Geologic Resources Division who proposed and designed this inventory selected the Greater Yellowstone Inventory and Monitoring Network (GRYN) as the pilot network for initiating this project. Through the research undertaken to identify the geologic type sections within the parks of the GRYN methodologies for data mining and reporting on these resources were established. Methodologies and reporting adopted for the GRYN have been used in the development of this type section inventory for the Klamath Inventory & Monitoring Network. The goal of this project is to consolidate information pertaining to geologic type sections which occur within NPS-administered areas, in order that this information is available throughout the NPS to inform park managers...
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Henderson, Tim, Mincent Santucci, Tim Connors, and Justin Tweet. National Park Service geologic type section inventory: Chihuahuan Desert Inventory & Monitoring Network. National Park Service, April 2021. http://dx.doi.org/10.36967/nrr-2285306.

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A fundamental responsibility of the National Park Service is to ensure that park resources are preserved, protected, and managed in consideration of the resources themselves and for the benefit and enjoyment by the public. Through the inventory, monitoring, and study of park resources, we gain a greater understanding of the scope, significance, distribution, and management issues associated with these resources and their use. This baseline of natural resource information is available to inform park managers, scientists, stakeholders, and the public about the conditions of these resources and the factors or activities which may threaten or influence their stability. There are several different categories of geologic or stratigraphic units (supergroup, group, formation, member, bed) which represent a hierarchical system of classification. The mapping of stratigraphic units involves the evaluation of lithologies, bedding properties, thickness, geographic distribution, and other factors. If a new mappable geologic unit is identified, it may be described and named through a rigorously defined process that is standardized and codified by the professional geologic community (North American Commission on Stratigraphic Nomenclature 2005). In most instances when a new geologic unit such as a formation is described and named in the scientific literature, a specific and well-exposed section of the unit is designated as the type section or type locality (see Definitions). The type section is an important reference section for a named geologic unit which presents a relatively complete and representative profile for this unit. The type or reference section is important both historically and scientifically, and should be recorded such that other researchers may evaluate it in the future. Therefore, this inventory of geologic type sections in NPS areas is an important effort in documenting these locations in order that NPS staff recognize and protect these areas for future studies. The documentation of all geologic type sections throughout the 423 units of the NPS is an ambitious undertaking. The strategy for this project is to select a subset of parks to begin research for the occurrence of geologic type sections within particular parks. The focus adopted for completing the baseline inventories throughout the NPS was centered on the 32 inventory and monitoring networks (I&M) established during the late 1990s. The I&M networks are clusters of parks within a defined geographic area based on the ecoregions of North America (Fenneman 1946; Bailey 1976; Omernik 1987). These networks share similar physical resources (geology, hydrology, climate), biological resources (flora, fauna), and ecological characteristics. Specialists familiar with the resources and ecological parameters of the network, and associated parks, work with park staff to support network level activities (inventory, monitoring, research, data management). Adopting a network-based approach to inventories worked well when the NPS undertook paleontological resource inventories for the 32 I&M networks. The network approach is also being applied to the inventory for the geologic type sections in the NPS. The planning team from the NPS Geologic Resources Division who proposed and designed this inventory selected the Greater Yellowstone Inventory and Monitoring Network (GRYN) as the pilot network for initiating this project. Through the research undertaken to identify the geologic type sections within the parks of the GRYN, methodologies for data mining and reporting on these resources was established. Methodologies and reporting adopted for the GRYN have been used in the development of this type section inventory for the Chihuahuan Desert Inventory & Monitoring Network. The goal of this project is to consolidate information pertaining to geologic type sections which occur within NPS-administered areas, in order that this information is available throughout the NPS...
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Henderson, Tim, Vincent Santucci, Tim Connors, and Justin Tweet. National Park Service geologic type section inventory: Northern Colorado Plateau Inventory & Monitoring Network. National Park Service, April 2021. http://dx.doi.org/10.36967/nrr-2285337.

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A fundamental responsibility of the National Park Service (NPS) is to ensure that park resources are preserved, protected, and managed in consideration of the resources themselves and for the benefit and enjoyment by the public. Through the inventory, monitoring, and study of park resources, we gain a greater understanding of the scope, significance, distribution, and management issues associated with these resources and their use. This baseline of natural resource information is available to inform park managers, scientists, stakeholders, and the public about the conditions of these resources and the factors or activities which may threaten or influence their stability. There are several different categories of geologic or stratigraphic units (supergroup, group, formation, member, bed) which represent a hierarchical system of classification. The mapping of stratigraphic units involves the evaluation of lithologies, bedding properties, thickness, geographic distribution, and other factors. If a new mappable geologic unit is identified, it may be described and named through a rigorously defined process that is standardized and codified by the professional geologic community (North American Commission on Stratigraphic Nomenclature 2005). In most instances when a new geologic unit such as a formation is described and named in the scientific literature, a specific and well-exposed section of the unit is designated as the type section or type locality (see Definitions). The type section is an important reference section for a named geologic unit which presents a relatively complete and representative profile. The type or reference section is important both historically and scientifically, and should be available for other researchers to evaluate in the future. Therefore, this inventory of geologic type sections in NPS areas is an important effort in documenting these locations in order that NPS staff recognize and protect these areas for future studies. The documentation of all geologic type sections throughout the 423 units of the NPS is an ambitious undertaking. The strategy for this project is to select a subset of parks to begin research for the occurrence of geologic type sections within particular parks. The focus adopted for completing the baseline inventories throughout the NPS was centered on the 32 inventory and monitoring networks (I&M) established during the late 1990s. The I&M networks are clusters of parks within a defined geographic area based on the ecoregions of North America (Fenneman 1946; Bailey 1976; Omernik 1987). These networks share similar physical resources (geology, hydrology, climate), biological resources (flora, fauna), and ecological characteristics. Specialists familiar with the resources and ecological parameters of the network, and associated parks, work with park staff to support network level activities (inventory, monitoring, research, data management). Adopting a network-based approach to inventories worked well when the NPS undertook paleontological resource inventories for the 32 I&M networks. The network approach is also being applied to the inventory for the geologic type sections in the NPS. The planning team from the NPS Geologic Resources Division who proposed and designed this inventory selected the Greater Yellowstone Inventory and Monitoring Network (GRYN) as the pilot network for initiating this project. Through the research undertaken to identify the geologic type sections within the parks of the GRYN methodologies for data mining and reporting on these resources was established. Methodologies and reporting adopted for the GRYN have been used in the development of this type section inventory for the Northern Colorado Plateau Inventory & Monitoring Network. The goal of this project is to consolidate information pertaining to geologic type sections which occur within NPS-administered areas, in order that this information is available throughout the NPS...
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Evans, Julie, Kendra Sikes, and Jamie Ratchford. Vegetation classification at Lake Mead National Recreation Area, Mojave National Preserve, Castle Mountains National Monument, and Death Valley National Park: Final report (Revised with Cost Estimate). National Park Service, October 2020. http://dx.doi.org/10.36967/nrr-2279201.

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Vegetation inventory and mapping is a process to document the composition, distribution and abundance of vegetation types across the landscape. The National Park Service’s (NPS) Inventory and Monitoring (I&M) program has determined vegetation inventory and mapping to be an important resource for parks; it is one of 12 baseline inventories of natural resources to be completed for all 270 national parks within the NPS I&M program. The Mojave Desert Network Inventory & Monitoring (MOJN I&M) began its process of vegetation inventory in 2009 for four park units as follows: Lake Mead National Recreation Area (LAKE), Mojave National Preserve (MOJA), Castle Mountains National Monument (CAMO), and Death Valley National Park (DEVA). Mapping is a multi-step and multi-year process involving skills and interactions of several parties, including NPS, with a field ecology team, a classification team, and a mapping team. This process allows for compiling existing vegetation data, collecting new data to fill in gaps, and analyzing the data to develop a classification that then informs the mapping. The final products of this process include a vegetation classification, ecological descriptions and field keys of the vegetation types, and geospatial vegetation maps based on the classification. In this report, we present the narrative and results of the sampling and classification effort. In three other associated reports (Evens et al. 2020a, 2020b, 2020c) are the ecological descriptions and field keys. The resulting products of the vegetation mapping efforts are, or will be, presented in separate reports: mapping at LAKE was completed in 2016, mapping at MOJA and CAMO will be completed in 2020, and mapping at DEVA will occur in 2021. The California Native Plant Society (CNPS) and NatureServe, the classification team, have completed the vegetation classification for these four park units, with field keys and descriptions of the vegetation types developed at the alliance level per the U.S. National Vegetation Classification (USNVC). We have compiled approximately 9,000 existing and new vegetation data records into digital databases in Microsoft Access. The resulting classification and descriptions include approximately 105 alliances and landform types, and over 240 associations. CNPS also has assisted the mapping teams during map reconnaissance visits, follow-up on interpreting vegetation patterns, and general support for the geospatial vegetation maps being produced. A variety of alliances and associations occur in the four park units. Per park, the classification represents approximately 50 alliances at LAKE, 65 at MOJA and CAMO, and 85 at DEVA. Several riparian alliances or associations that are somewhat rare (ranked globally as G3) include shrublands of Pluchea sericea, meadow associations with Distichlis spicata and Juncus cooperi, and woodland associations of Salix laevigata and Prosopis pubescens along playas, streams, and springs. Other rare to somewhat rare types (G2 to G3) include shrubland stands with Eriogonum heermannii, Buddleja utahensis, Mortonia utahensis, and Salvia funerea on rocky calcareous slopes that occur sporadically in LAKE to MOJA and DEVA. Types that are globally rare (G1) include the associations of Swallenia alexandrae on sand dunes and Hecastocleis shockleyi on rocky calcareous slopes in DEVA. Two USNVC vegetation groups hold the highest number of alliances: 1) Warm Semi-Desert Shrub & Herb Dry Wash & Colluvial Slope Group (G541) has nine alliances, and 2) Mojave Mid-Elevation Mixed Desert Scrub Group (G296) has thirteen alliances. These two groups contribute significantly to the diversity of vegetation along alluvial washes and mid-elevation transition zones.
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Galvin, Jeff, and Sarah Strudd. Vegetation inventory, mapping, and characterization report, Saguaro National Park: Volume II, association summaries. Edited by Alice Wondrak Biel. National Park Service, March 2021. http://dx.doi.org/10.36967/nrr-2284793.

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The Sonoran Desert Network (SODN) conducted a vegetation mapping and characterization effort at the two districts of Saguaro National Park from 2010 to 2018. This project was completed under the National Park Service (NPS) Vegetation Mapping Inventory, which aims to complete baseline mapping and classification inventories at more than 270 NPS units. The vegetation map data were collected to provide park managers with a digital map product that meets national standards of spatial and thematic accuracy, while also placing the vegetation into a regional and national context. A total of 97 distinct vegetation communities were described: 83 exclusively at the Rincon Mountain District, 9 exclusively at the Tucson Mountain District, and 5 occurring in both districts. These communities ranged from low-elevation creosote (Larrea tridentata) shrub-lands spanning broad alluvial fans to mountaintop Douglas fir (Pseudotsuga menziesii) forests on the slopes of Rincon Peak. All 97 communities were described at the association level, each with detailed narratives including lists of species found in each association, their abundance, landscape features, and overall community structural characteristics. Only 15 of the 97 vegetation types were existing “accepted” types within the National Vegetation Classification (NVC). The others are newly described and specific to Saguaro National Park (and will be proposed for formal status within the NVC). This document is Volume II of three volumes comprising the Saguaro National Park Vegetation Mapping Inventory. This volume provides two-page summaries of the 97 associations identified and mapped during the project, and detailed in Volume I. Summaries are presented by district, starting with the Tucson Mountain District. These summaries are abridged versions of the full association descriptions found in Volume III.
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Galvin, Jeff, and Sarah Studd. Vegetation inventory, mapping, and characterization report, Saguaro National Park: Volume III, type descriptions. Edited by Alice Wondrak Biel. National Park Service, March 2021. http://dx.doi.org/10.36967/nrr-2284802.

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The Sonoran Desert Network (SODN) conducted a vegetation mapping and characterization effort at the two districts of Saguaro National Park from 2010 to 2018. This project was completed under the National Park Service (NPS) Vegetation Mapping Inventory, which aims to complete baseline mapping and classification inventories at more than 270 NPS units. The vegetation map data were collected to provide park managers with a digital map product that meets national standards of spatial and thematic accuracy, while also placing the vegetation into a regional and national context. A total of 97 distinct vegetation communities were described: 83 exclusively at the Rincon Mountain District, 9 exclusively at the Tucson Mountain District, and 5 occurring in both districts. These communities ranged from low-elevation creosote (Larrea tridentata) shrub-lands spanning broad alluvial fans to mountaintop Douglas fir (Pseudotsuga menziesii) forests on the slopes of Rincon Peak. All 97 communities were described at the association level, each with detailed narratives including lists of species found in each association, their abundance, landscape features, and overall community structural characteristics. Only 15 of the 97 vegetation types were existing “accepted” types within the NVC. The others are newly de-scribed and specific to Saguaro National Park (and will be proposed for formal status within the NVC). This document is Volume III of three volumes comprising the Saguaro National Park Vegetation Mapping Inventory. This volume provides full type descriptions of the 97 associations identified and mapped during the project, and detailed in Volume I. Volume II provides abridged versions of these full descriptions, briefly describing the floristic and structural characteristics of the vegetation and showing representative photos of associations, their distribution, and an example of the satellite imagery for one polygon.
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Ramm-Granberg, Tynan, F. Rocchio, Catharine Copass, Rachel Brunner, and Eric Nelsen. Revised vegetation classification for Mount Rainier, North Cascades, and Olympic national parks: Project summary report. National Park Service, February 2021. http://dx.doi.org/10.36967/nrr-2284511.

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Field crews recently collected more than 10 years of classification and mapping data in support of the North Coast and Cascades Inventory and Monitoring Network (NCCN) vegetation maps of Mount Rainier (MORA), Olympic (OLYM), and North Cascades (NOCA) National Parks. Synthesis and analysis of these 6000+ plots by Washington Natural Heritage Program (WNHP) and Institute for Natural Resources (INR) staff built on the foundation provided by the earlier classification work of Crawford et al. (2009). These analyses provided support for most of the provisional plant associations in Crawford et al. (2009), while also revealing previously undescribed vegetation types that were not represented in the United States National Vegetation Classification (USNVC). Both provisional and undescribed types have since been submitted to the USNVC by WNHP staff through a peer-reviewed process. NCCN plots were combined with statewide forest and wetland plot data from the US Forest Service (USFS) and other sources to create a comprehensive data set for Washington. Analyses incorporated Cluster Analysis, Nonmetric Multidimensional Scaling (NMS), Multi-Response Permutation Procedure (MRPP), and Indicator Species Analysis (ISA) to identify, vet, and describe USNVC group, alliance, and association distinctions. The resulting revised classification contains 321 plant associations in 99 alliances. A total of 54 upland associations were moved through the peer review process and are now part of the USNVC. Of those, 45 were provisional or preliminary types from Crawford et al. (2009), with 9 additional new associations that were originally identified by INR. WNHP also revised the concepts of 34 associations, wrote descriptions for 2 existing associations, eliminated/archived 2 associations, and created 4 new upland alliances. Finally, WNHP created 27 new wetland alliances and revised or clarified an additional 21 as part of this project (not all of those occur in the parks). This report and accompanying vegetation descriptions, keys and synoptic and environmental tables (all products available from the NPS Data Store project reference: https://irma.nps.gov/DataStore/Reference/Profile/2279907) present the fruit of these combined efforts: a comprehensive, up-to-date vegetation classification for the three major national parks of Washington State.
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