This thesis examines the concept of time series forecasting. More specifically, it predicts the load and power demand in Sulaymaniyah, Iraqi Kurdistan, who are today experiencing frequent power shortages. This study applies a commonly used time series model, the autoregressive integrated moving average model, which is compared to the naïve method. Several key model properties are inspected to evaluate model accuracy. The model is then used to forecast the load and the demand on a daily, weekly and monthly basis. The forecasts are evaluated by examining the residual metrics. Furthermore, the quantitative results and the answers collected from interviews are used as a basis to investigate the conditions of capacity planning in order to determine a suitable strategy to minimize the unserved power demand. The findings indicate an unsustainable over consumption of power in the region due to low tariffs and subsidized energy. A suggested solution is to manage power demand by implementing better strategies such as increasing tariffs and to use demand forecast to supply power accordingly. The monthly supply forecast in this study outperforms the baseline method but not the demand forecast. On weekly basis, both the load and the demand models underperform. The performance of the daily forecasts performs equally or worse than the baseline. Overall, the supply predictions are more precise than the demand predictions. However, there is room for improvement regarding the forecasts. For instance, better model selection and data preparation can result in more accurate forecasts. / Denna studie undersöker prediktion av tidserier. Den tittar närmare på last- och effektbehov i Sulaymaniyah i Irak som idag drabbas av regelbunden effektbrist. Rapporten applicerar en vedertagen tidseriemodell, den autoregressiva integrerade glidande medelvärdesmodellen, som sedan jämförs med den naiva metoden. Några karaktäristiska modellegenskaper undersöks för att evaluera modellens noggrannhet. Den anpassade modellen används sedan för att predikera last- och effektbehovet på dags-, månads-, och årsbasis. Prognoserna evalueras genom att undersöka dess residualer. Vidare så användas de kvalitativa svaren från intervjuerna som underlag för att undersöka förutsättningarna för kapacitetsplanering och den strategi som är bäst lämpad för att möta effektbristen. Studien visar att det råder en ohållbar överkonsumtion av energi i regionen som konsekvens av låga elavgifter och subventionerad energi. En föreslagen lösning är att hantera efterfrågan genom att implementera strategier som att höja elavgifter men även försöka matcha produktionen med efterfrågan med hjälp av prognoser. De månadsvisa prognoserna för produktionen i studien överträffar den naiva metoden men inte för prognoserna för efterfrågan. På veckobasis underpresterar båda modellerna. De dagliga prognoserna presterar lika bra eller värre än den naiva metoden. I sin helhet lyckas modellerna förutspå utbudet bättre än efterfrågan på effekt. Men det finns utrymme för förbättringar. Det går nog att uppnå bättre resultat genom bättre förbehandling av data och noggrannare valda tidseriemodeller.

中國經濟崛起後，台灣製造業者面臨比以往更激烈的競爭，急需提升自身能力，為了能有效對抗複雜、變化快速的環境，企業應從既有的競爭優勢建立和延伸，而台灣的經濟自由以及完善的製造業產能，是製造業競爭力提升的關鍵。在產能規劃時容易因為客戶影響而產生產能平滑化議題，其中以季節性產品製造商為最，且現今產品生命週期縮短及客戶喜好改變快速，導致市場不確定性提高，企業的產能運用越來越容易受客戶需求之影響，因此了解既有客戶資訊並將其納入產能平滑化策略之考量因素，是現今台灣季節性產品製造商發展優勢的重要議題。然而目前客戶分析之應用大多在銷售領域，結合產能規劃策略的研究及個案都相當不足，若能建立兩者結合之研究分析及個案討論，會更有助於未來提升台灣製造業競爭力之研究，因此本研究探討客戶分析對產能平滑化策略之影響。 本研究利用個案研究法分析世界第四大冷氣壓縮機製造商－瑞智精密公司，探討其如何在2011年至2014年期間將客戶分析導入產能規劃策略，並透過內部銷售數據、瑞智專業顧問訪談以及第三機構之研究/學術資料三個資料來源進行三角檢定，評估其在淡季時是否有助增加銷售量；旺季時是否可以增加產量或是發展其他產能分配策略。 本研究以實務資料驗證結合客戶分析之產能平滑化策略是否具備實質效益，研究發現導入客戶分析之產能平滑化策略確實縮小了淡旺季差異，也可發展出客戶評價機制方案進行旺季產能分配策略，而將客戶分析和客戶評價機制導入產能規劃步驟，可以讓客戶資訊從銷售部門流通至生產部門，化解兩者之間目標不同的衝突，使企業內部能更有效率地溝通合作，迅速反應客戶需求創造競爭力。 / After the rising of economy in China, the manufacturers in Taiwan are facing fierce horizontal competition. In order to secure their leading position and competitiveness in the market, Taiwanese manufacturers have to enhance and develop their current competitive advantages to further respond to the complicated and volatile economic environment quickly. Priority should be given to enhance the capacity planning as the economic freedom and sufficient manufacturing capacity are two main factors making the manufacturers to be competitive and successful in Taiwan. However, the capacity planning is easily influenced by the customers, which caused an issue called “Production Smoothing”. The problem is obvious and complicated for those seasonal product manufacturers. Moreover, the shorter product lifecycle and rapidly changing customer preferences contribute to the uncertainty in the market. As a result, the capacity planning is now more susceptible to be affected by customers’ needs. That is why it is very critical for the manufacturers to understand their customers’ needs and further to consider the needs in their company’s capacity plans. However, the current case study of customer analysis usually focuses on the field of marketing instead of on the capacity planning. It would be great if we could combine the capacity planning and marketing to the case discussion and analysis, further to help develop the research on the competitiveness of Taiwanese manufacturers. Therefore, the object of this article is to analyze how the customer analysis can bring an impact to the company’s capacity smoothing strategy. This case study is to analyze Rechi Precision Company, the world's fourth largest air conditioner compressor manufacturers, discussing how they take customer analysis into consideration when they develop the capacity strategy from 2011 to 2014. By analyzing internal sales data, interviewing with the internal consultants in Rechi, and referring research from the third institutions, we access whether the combination of customer analysis and capacity planning could help increase the sales during the low season and increase the capacity or develop other capacity allocation strategy during the peak season. According to the research results, the combination can decrease sales difference between the peak season and the low season. It can also help develop customer evaluation mechanism to determine capacity allocation. In addition, in order to respond to customers’ needs quickly, the manufacturers should integrate customer analysis and customer evaluation mechanism into capacity planning steps, which can soften the conflicts between the sales and production department. All of these efforts could make the whole company communicate and cooperate with each other more efficient.

O planejamento de experimentos em sistemas computacionais não é uma tarefa trivial, pois envolve diversas etapas tais como, o planejamento propriamente dito, a execução dos experimentos e a análise dos resultados. A definição e a utilização de metodologias adequadas para cada uma destas etapas facilita a obtenção dos resultados de um experimento em um sistema computacional. Neste trabalho são apresentados mecanismos para auxiliar o planejamento e execução de experimentos em sistemas orientados a serviços. O planejamento de experimento é realizado a partir de um modelo baseado nos conjuntos de entradas comuns a arquiteturas orientadas a serviço. A execução deste planejamento é feita em um ambiente colaborativo real, a qual auxilia a identificação de gargalos que não estão presentes em simulações ou modelos analíticos. Um estudo de caso aplicado na arquitetura WSARCH, possibilitou avaliar seu desempenho e identificar problemas de configuração / The design of experiments in computational systems is not a trivial task as it involves several steps such as planning and execution of the experiments and the analyse of the results. The use of appropriate methodologies for each of these steps makes it easier obtain the experiment results of a computer system. In this dissertation, mechanisms to assist the planning and execution of experiments in service-oriented systems are presented. The planning of the experiment is made according to a model based on a set of common entries for service-oriented architectures. The experiment execution is performed in a real collaborative environment, which helps to identify bottlenecks that are not found in simulations or analytical models. A study case applied in WSARCH architecture, enables to evaluate the performance and identify configuration problems

O planejamento de experimentos em sistemas computacionais não é uma tarefa trivial, pois envolve diversas etapas tais como, o planejamento propriamente dito, a execução dos experimentos e a análise dos resultados. A definição e a utilização de metodologias adequadas para cada uma destas etapas facilita a obtenção dos resultados de um experimento em um sistema computacional. Neste trabalho são apresentados mecanismos para auxiliar o planejamento e execução de experimentos em sistemas orientados a serviços. O planejamento de experimento é realizado a partir de um modelo baseado nos conjuntos de entradas comuns a arquiteturas orientadas a serviço. A execução deste planejamento é feita em um ambiente colaborativo real, a qual auxilia a identificação de gargalos que não estão presentes em simulações ou modelos analíticos. Um estudo de caso aplicado na arquitetura WSARCH, possibilitou avaliar seu desempenho e identificar problemas de configuração / The design of experiments in computational systems is not a trivial task as it involves several steps such as planning and execution of the experiments and the analyse of the results. The use of appropriate methodologies for each of these steps makes it easier obtain the experiment results of a computer system. In this dissertation, mechanisms to assist the planning and execution of experiments in service-oriented systems are presented. The planning of the experiment is made according to a model based on a set of common entries for service-oriented architectures. The experiment execution is performed in a real collaborative environment, which helps to identify bottlenecks that are not found in simulations or analytical models. A study case applied in WSARCH architecture, enables to evaluate the performance and identify configuration problems

A crescente complexidade das redes de comunicação de dados tem como conseqüência direta tornar cada vez mais complexas as tarefas de projetar seu dimensionamento e evolução. Um passo preliminar vitalmente importante no projeto de uma rede é a coleta de dados relacionados ao uso esperado da rede. Os padrões de tráfego estimados são usados nos cálculos de dimensionamento dos recursos. Fortemente relacionada a estas atividades está a previsão da performance em termos de throughput da rede, tempos de resposta, probabilidade de congestionamento, entre outras. Uma análise de performance efetiva depende de se representar precisamente a configuração da rede e da carga de tráfego a ela submetida. Técnicas de modelagem analítica ou de simulação podem ser usadas para determinar a performance esperada do sistema. Neste trabalho a usada a técnica de simulação para modelar o tráfego da rede usando dados coletados em uma rede real por monitoração. Trabalhando-se com o modelo validado e possível ajustar a carga de tráfego para representar mudanças esperadas nos volumes de tráfego, e testar o efeito na performance de diferentes configurações de rede. Isso possibilita que os processos de planejamento e projeto sejam executados com confiança, alem dos custos da rede poderem ser otimizados. O sistema apresentado neste trabalho e orientado à gerência de performance de redes, apoiando as atividades de gerência e planejamento de capacidade. Defende-se a idéia de que, a partir do perfil dos usuários de uma rede, derivado do tráfego por eles gerado, pode-se construir um modelo de tráfego significativamente representativo para a análise e previsão do desempenho da rede. O modelo foi desenvolvido para redes de comutação de pacotes com serviço orientado a conexão, e validado sobre o tráfego de uma rede X.25 através de um modelo de simulação, implementado em GPSS. O protótipo do sistema é composto por três processos principais que incorporam as etapas da análise de performance: monitoração do tráfego, análise do tráfego e simulação do tráfego. Na monitoração, são contabilizadas uma série de variáveis para cada conexão gerada na rede. Para cada tipo de aplicação são calculados os respectivos fatores de carga de tráfego. As aplicações são classificadas em dois grandes grupos: interativas e não-interativas. O processo de análise do tráfego gera os fatores de carga de tráfego na forma de tabelas e gráficos. As conexões e as métricas de performance produzidas na simulação do tráfego podem ser analisadas e validadas graficamente. O sistema proposto foi especificado em SDL (Specification and Description Language). / The increasing complexity of communication networks turns each time more complex the task to plan its expansion and evolution. A vitally important preliminar step in computer network design is the gathering of data relating to the expected use of the network. The estimated traffic patterns are used in resource usage computations. Closely related to these activities is the estimation of performance in terms of network throughput, response times, congestion probability, among others. An efective performance analysis requires the accurate representation of computer network configuration and traffic load. Analytical or simulation techniques can be used to establish the expected system performance. This work makes use of simulation to model the network traffic, based on collected data of a real network. network. Working with the validated model is possible to adjust the traffic load to represent future demand, and to test the performance impact under distinct network configurations. This enable a trustful execution of network planning and design, besides of the cost optimization. The system presented at this work is network performance management oriented, giving support to capacity management and capacity planning. The central idea is that, through network users profile achieved from generated traffic, it's possible to build a representative traffic model to aim at the network performance analysis and forecast. The model was developed to connection oriented packet switched networks, and validated by means of a simulation model to X.25 network traffic, implementd in GPSS. The system prototype comprises three process: traffic monitoring, traffic analysis and traffic simulation. In monitoring, a set of variables are registered for each network connection generated. The traffic load factors are computed according the application type. The applications are classified in two groups: interactive and non-interactive. The traffic analysis process produces traffic load factors in form of tables and graphics. Connections and performance metrics generated at traffic simulation can be graphically analyzed and validated. The proposed system was specified in SDL (Specification and Description Language).

L’informatique en nuage révolutionne complètement la façon de gérer les ressources. Grâce à l’élasticité, les ressources peuvent être provisionnées en quelques minutes pour satisfaire un niveau de qualité de service (QdS) formalisé par un accord de niveau de service (SLA) entre les différents acteurs du nuage. Le principal défi des fournisseurs de services est de maintenir la satisfaction de leurs consommateurs tout en minimisant le coût de ces services. Du point de vue SaaS, ce défi peut être résolu d’une manière ad-hoc par l’allocation/-libération des ressources selon un ensemble de règles prédéfinies avec Amazon Auto Scaling par exemple. Cependant, implémenter finement ces règles d’élasticité n’est pas une tâche triviale. D’une part, la difficulté de profiler la performance d’un service compromet la précision de la planification des ressources. D’autre part, plusieurs paramètres doivent être pris en compte, tels que la multiplication des types de ressources, le temps non-négligeable d’initialisation de ressource et le modèle de facturation IaaS. Cette thèse propose une solution complète pour la gestion des contrats de service du nuage. Nous introduisons CSLA (Cloud ServiceLevel Agreement), un langage dédié à la définition de contrat de service en nuage. Il adresse finement les violations SLA via la dégradation fonctionnelle/QdS et des modèles de pénalité avancés. Nous proposons, ensuite, HybridScale un framework de dimensionnement automatique dirigé par les SLA. Il implémente l’élasticité de façon hybride : gestion réactive-proactive, dimensionnement vertical horizontal et multi-couches (application-infrastructure). Notre solution est validée expérimentalement sur Amazon EC2. / Cloud computing promises to completely revolutionize the way to manage resources. Thanks to elasticity, resources can be provisioning within minutes to satisfy a required level of Quality of Service(QoS) formalized by Service Level Agreements (SLAs) between different Cloud actors. The main challenge of service providers is to maintain its consumer’s satisfaction while minimizing the service costs due to resources fees. For example, from the SaaS point of view, this challenge can be achieved in ad-hoc manner by allocating/releasing resources based on a set of predefined rules as Amazon Auto Scaling implements it. However, doing it right –in a way that maintains end-users satisfaction while optimizing service cost– is not a trivial task. First, because of the difficulty to profile service performance,the accuracy of capacity planning may be compromised. Second, several parameters should be taken into account such as multiple resource types, non-ignorable resource initiation time and IaaS billing model. For that purpose, we propose a complete solution for Cloud Service Level Management. We first introduce CSLA (Cloud Service LevelAgreement), a specific language to describe SLA for Cloud services. It finely expresses SLA violations via functionality/QoS degradationand an advanced penalty model. Then, we propose HybridScale, an auto-scaling framework driven by SLA. It implements the Cloud elasticity in a triple hybrid way : reactive-proactive management, vertical horizontal scaling at cross-layer (application-infrastructure). Our solution is experimentally validated on Amazon EC2.

This research focuses on large-scale manufacturing systems having a number of stations with multiple tools and product types with different and deterministic processing steps. The objective is to determine the production quantities of multiple products and the tool requirements of each station that maximizes net profit while satisfying strategic constraints such as cycle times, required throughputs, and investment. The formulation of the problem, named OptiProfit, is a mixed-integer nonlinear programming (MINLP) with the stochastic issues addressed by mean-value analysis (MVA) and queuing network models. Observing that OptiProfit is an NP-complete, nonconvex, and nonmonotonic problem, the research develops a heuristic method, Differential Coefficient Based Search (DCBS). It also performs an upper-bound analysis and a performance comparison with six variations of Greedy Ascent Procedure (GAP) heuristics and Modified Simulated Annealing (MSA) in a number of randomized cases. An example problem based on a semiconductor manufacturing minifab is modeled as an OptiProfit problem and numerically analyzed. The proposed methodology provides a very good quality solution for the high-level design and operation of manufacturing facilities.

In this thesis, by being motivated from the challenges in perinatal networks, we address design, evaluation and flow control of a stochastic healthcare network where there exist multiple levels of hospitals and different types of patients. Patients are supposed urgent; thus they can be rejected and overflow to another facility in the same network if no service capacity is available at their arrival. Rejection of patients due to the lack of service capacity is the common phenomenon in overflow networks. We approach the problem from both strategic and operational perspectives. In strategic part, we address a location & capacity planning problem for adjusting the network to better meet demographic changes. In operational part, we study the optimal patient admission control policies to increase flexibility in allocation of resources and improve the control of patient flow in the network. Finally, in order to evaluate the performance of the network, we develop new approximation methodologies that estimate the rejection probabilities in each hospital for each arriving patient group, thus the overflow probabilities among hospitals. Furthermore, an agent-based discrete-event simulation model is constructed to adequately represent our main applicationarea: Nord Hauts-de-Seine Perinatal Network. The simulation model is used to evaluate the performance of the complex network and more importantly evaluate the strength of the optimal results of our analytical models. The developed methodologies in this thesis are combined in a decision support tool, foreseen under the project "COVER", which aims to assist health system managers to effectively plan strategic and operational decisions of a healthcare network and evaluate the performance of their decisions.

Thesis (MScEng (Industrial Engineering))--University of Stellenbosch, 2010. / ENGLISH ABSTRACT: The purpose of this study is to investigate the capacity of a proposed bus rapid transit (BRT) station in Cape Town. A bus rapid transit system is a high-capacity public transportation system that carries passengers from one point to another, providing a service that is faster and more efficient than an ordinary bus line. The implementation of these systems is increasing rapidly worldwide, serving as a solution to decrease traffic congestion. The capacity of the proposed bus station, known as the Thibault Station, is investigated in the study by developing a simulation model. The aim is to develop a stochastic simulation model, which represents the flow of passengers throughout the station so that the station capacity can be investigated. By developing a stochastic model as opposed to a deterministic model, elements of uncertainty can be included into the model, thereby representing a system that is closer to the real-life situation under investigation. The majority of BRT systems, as well as past studies undertaken on the Thibault Station, are designed using deterministic calculations. The study commences by researching literature on BRT systems and focuses on the current methods used to calculate station capacity requirements. Thereafter, the concept of simulation is introduced. Simulation is the method chosen to model and evaluate the passenger and bus operations at the Thibault Station. The study presents the methods used to build and verify the simulation model. This is done to familiarise the user with a number of aspects of the model. The model can then be used as a tool to investigate capacity parameters and alternative designs or scenarios. Using the results of these investigations, decisions can ultimately be made regarding the planning and design components of any bus rapid transit station given that the model is adapted. Scenario results, as well as interpretations of performance measurements, are presented at the end of the study. The results can be used for more realistic design of BRT stations using stochastic modelling. / AFRIKAANSE OPSOMMING: Die doel van die studie is om ondersoek in te stel na die kapasiteit van „n hoëspoed bus vervoer stelsel (BRT). Die ondersoek is gebaseer op „n voorgestelde bus stelsel vir Kaapstad. „n BRT-stelsel is „n hoë-kapasiteit publieke vervoerstelsel wat passasiers van een punt na „n ander vervoer, deur „n diens te verskaf wat vinniger en meer doeltreffend is as „n gewone bus stelsel. Die implementering van hierdie tipe stelsels neem wêreldwyd toe en dien as „n oplossing om verkeersopeenhopings te verminder. Die spesifieke busstasie wat ondersoek word staan bekend as die Thibault Stasie van Kaapstad se BRT-stelsel. Die kapasiteit van die stasie word ondersoek deur middel van simulasiemodellering. Die doel is om „n stogastiese simulasiemodel wat die vloei van passasiers modelleer te ontwikkel ten einde die kapasiteit van die stasie te ondersoek. Deur „n stogastiese model in plaas van „n deterministiese model te gebruik, kan elemente van onsekerheid ingesluit word. Dit verteenwoordig dus „n stelsel wat nader aan die werklikheid is. Tans word meeste BRT-stelsels ontwerpe gebaseer op deterministiese berekeninge, asook historiese studies wat onderneem is oor die Thibault Stasie. Die studie begin deur literatuur oor BRT-stelsels te bestudeer en fokus daarna op die huidige metodes wat gebruik word om die vereiste kapasiteit van „n busstasie te bepaal. Die konsep van simulasie word daarna voorgestel. Simulasie is die metode wat in die studie gebruik word om die passasier- en busaktiwiteite van die Thibault Stasie te modelleer en te evalueer. Die studie verskaf die metodes wat gebruik word vir die ontwikkeling en geldigmaak van die simulasiemodel. Gebruikers word op dié manier blootgestel aan die verskillende aspekte van die model. Nadat die gebruikers vertroud is met sekere aspekte van die model, word die model verder uiteengesit en word daar verduidelik hoe dit as „n instrument om kapasiteit parameters en alternatiewe ontwerpe van busstasies te ondersoek kan dien. Die resultate van die model kan gebruik word om beplannings- en ontwerpbesluite van enige busstasie te neem. Aan die einde van die studie word scenarioresultate bekendgestel, asook die interpretasie daarvan. Die resultate kan gebruik word vir meer realistiese ontwerp van BRT-stasies met behulp van stogastiese simulasie modellering.

A crescente complexidade das redes de comunicação de dados tem como conseqüência direta tornar cada vez mais complexas as tarefas de projetar seu dimensionamento e evolução. Um passo preliminar vitalmente importante no projeto de uma rede é a coleta de dados relacionados ao uso esperado da rede. Os padrões de tráfego estimados são usados nos cálculos de dimensionamento dos recursos. Fortemente relacionada a estas atividades está a previsão da performance em termos de throughput da rede, tempos de resposta, probabilidade de congestionamento, entre outras. Uma análise de performance efetiva depende de se representar precisamente a configuração da rede e da carga de tráfego a ela submetida. Técnicas de modelagem analítica ou de simulação podem ser usadas para determinar a performance esperada do sistema. Neste trabalho a usada a técnica de simulação para modelar o tráfego da rede usando dados coletados em uma rede real por monitoração. Trabalhando-se com o modelo validado e possível ajustar a carga de tráfego para representar mudanças esperadas nos volumes de tráfego, e testar o efeito na performance de diferentes configurações de rede. Isso possibilita que os processos de planejamento e projeto sejam executados com confiança, alem dos custos da rede poderem ser otimizados. O sistema apresentado neste trabalho e orientado à gerência de performance de redes, apoiando as atividades de gerência e planejamento de capacidade. Defende-se a idéia de que, a partir do perfil dos usuários de uma rede, derivado do tráfego por eles gerado, pode-se construir um modelo de tráfego significativamente representativo para a análise e previsão do desempenho da rede. O modelo foi desenvolvido para redes de comutação de pacotes com serviço orientado a conexão, e validado sobre o tráfego de uma rede X.25 através de um modelo de simulação, implementado em GPSS. O protótipo do sistema é composto por três processos principais que incorporam as etapas da análise de performance: monitoração do tráfego, análise do tráfego e simulação do tráfego. Na monitoração, são contabilizadas uma série de variáveis para cada conexão gerada na rede. Para cada tipo de aplicação são calculados os respectivos fatores de carga de tráfego. As aplicações são classificadas em dois grandes grupos: interativas e não-interativas. O processo de análise do tráfego gera os fatores de carga de tráfego na forma de tabelas e gráficos. As conexões e as métricas de performance produzidas na simulação do tráfego podem ser analisadas e validadas graficamente. O sistema proposto foi especificado em SDL (Specification and Description Language). / The increasing complexity of communication networks turns each time more complex the task to plan its expansion and evolution. A vitally important preliminar step in computer network design is the gathering of data relating to the expected use of the network. The estimated traffic patterns are used in resource usage computations. Closely related to these activities is the estimation of performance in terms of network throughput, response times, congestion probability, among others. An efective performance analysis requires the accurate representation of computer network configuration and traffic load. Analytical or simulation techniques can be used to establish the expected system performance. This work makes use of simulation to model the network traffic, based on collected data of a real network. network. Working with the validated model is possible to adjust the traffic load to represent future demand, and to test the performance impact under distinct network configurations. This enable a trustful execution of network planning and design, besides of the cost optimization. The system presented at this work is network performance management oriented, giving support to capacity management and capacity planning. The central idea is that, through network users profile achieved from generated traffic, it's possible to build a representative traffic model to aim at the network performance analysis and forecast. The model was developed to connection oriented packet switched networks, and validated by means of a simulation model to X.25 network traffic, implementd in GPSS. The system prototype comprises three process: traffic monitoring, traffic analysis and traffic simulation. In monitoring, a set of variables are registered for each network connection generated. The traffic load factors are computed according the application type. The applications are classified in two groups: interactive and non-interactive. The traffic analysis process produces traffic load factors in form of tables and graphics. Connections and performance metrics generated at traffic simulation can be graphically analyzed and validated. The proposed system was specified in SDL (Specification and Description Language).