Proposal for an Object Oriented Process Modeling Language

Processes are very important for the success within many business fields. They define the proper application of methods, technologies and company structures in order to reach business goals. Not only manufacturing processes have to be defined from the start point to their end, also other processes like product development processes need a proper description to gain success. For example in automotive industries complex product development processes are necessary and defined prior to product development. Over the last decades several product modeling languages have been developed moving to object oriented modeling languages, such as UML, but the used process modeling languages are still procedural. The paradigm shift caused by object oriented description within product modeling languages has to be transferred to process modeling languages. This paper introduces an object oriented approach for process modeling. Using UML as a starting point an object oriented process modeling method is differentiated. The basic concepts which are needed for process modeling are put into an object oriented context and are explained. The paper also deals with the most important methods behind object oriented process modeling and gives an outlook, what can be achieved by this approach

Beyond Control-Flow: Extending Business Process Configuration to Roles and Objects

A configurable process model is an integrated representation of multiple variants of a business process. It is designed to be individualized to meet a particular set of requirements. As such, configurable process models promote systematic reuse of proven or common practices. Existing notations for configurable process modeling focus on capturing tasks and control-flow dependencies, neglecting equally important aspects of business processes such as data flow, material flow and resource management. This paper fills this gap by proposing an integrated meta-model for configurable processes with advanced features for capturing resources involved in the performance of tasks (through task-role associations) as well as flow of data and physical artifacts (through task-object associations). Although embodied as an extension of a popular process modeling notation, namely EPC, the meta-model is defined in an abstract and formal manner to make it applicable to other notations

A Model of Electronic Document Management System for Limited Partnership

Both types of documents, electronic and non-electronic are a major component supporting activities.  In addition to the documents, communications capabilities to employees and managers effectively with other stakeholders are one of the important key achievements of organizational goals.  LP. XYZ is one of the Consultants in the field of Information Technology, but the storage and management of electronic documents and archives themselves carried on a server without a management information system, so that records and electronic documents have not been properly managed. This study makes modeling system includes document management of process models, data models and interface models to suit the needs of the LP. XYZ administration in organizing activities, such as enterprise document management, web content management, project management and communication management of work, so the management information system may be supporting the business activities and operations of LP. XYZ

Automated Test Case Generation Model from UML Diagrams based on Monotonic Genetic Algorithm

The procedure of developing package includes software testing as an imperative phase. The three components of the testing process are test execution, test evaluation and test case generation. The creation of test cases remains at the heart of challenging automation. It decreases the amount of mistakes and flaws while saving time and effort. A new way to automate the testing process has been developed to reduce the high tot test evaluation al of software testing and to improve the dependability of the testing procedures. In this paper, a innovative technique for creating and refining test cases using UML Activity Chart diagrams is proposed. The Genetic Algorithm's crossover method was used to create the new test sequence, and the test sequences' effectiveness was assessed by Mutation Analysis. As a result, they are unable to effectively combat multilayer perceptrons when faced with incorrect properties. Monotonic genetic algorithm is a Concept that is easy to understand and Supports multi-objective. The radial basis function (RBF) neural network algorithm currently in use has challenges counting the amount of neurons in the hidden layer and has poor weight learning ability from the hidden layer to the output layer. RBF networks have the drawback of giving respectively attribute a comparable weight since all factors are taken into account equally while calculating distance unless the attribute weight parameters are included in the entire optimization procedure

Forecasting model development and application in the aviation industry

Forecasting models have been applied to many industries as a decision-making tool for over 100 years. Their application in the aviation industry benefits a wide variety of stakeholders such as airliners and airport authorities, who use past data to predict demand and passenger choices so that they can better define fares, manage their fleet and make decisions on the airport layout and future expansions, among others. The main objective of this dissertation is the development of a forecasting model capable of predicting the number of flight movements at Lisbon Airport. The model was based on an autoregressive model, which uses past data in order to forecast future figures. Weekly data regarding the flight movements at Lisbon Airport was the sample for this study, which was processed through RStudio programming software. Once the Autoregressive Moving Average (ARIMA) models were defined, the forecasting data was created and further tested for accuracy using extant data. The impact of COVID-19 had to be considered in this situation, leading to the breakdown of the original time-series into three different samples. The forecasting models were subsequently created through each of these models. The results were expressed through the three different models, and since two of them have extant data, meaning an existing sample to compare the predicted data, it was possible to determine the accuracy level. However, these models cannot be applied immediately since the impact of COVID-19 is still present and flights have not resumed normality. Once this normality resumes, the models can be applied.Modelos preditivos têm sido aplicados a variados setores como ferramenta de tomada de decisão há mais de 100 anos. A sua aplicação na indústria aeronáutica beneficia uma ampla variedade de interessados, como companhias aéreas e autoridades aeroportuárias que utilizam dados para prever a procura, definir preços, gerir frotas e tomar decisões relativas ao layout do aeroporto, expansões futuras, entre outros. O principal objetivo desta dissertação é o desenvolvimento de um modelo de previsão capaz de prever o número de movimentos de voos no Aeroporto de Lisboa. O modelo foi baseado num modelo autorregressivo, que utiliza dados passados para prever valores futuros. O Aeroporto de Lisboa foi o objeto escolhido para esta dissertação. Dados semanais relativos aos movimentos aéreos no Aeroporto de Lisboa consistiram na amostra para este estudo, os quais foram processados através do software de programação RStudio. Assim que os modelos Autoregressive Moving Average (ARIMA) foram definidos, os dados de previsão foram criados e testados quanto à precisão usando os dados existentes. O impacto do COVID-19 teve que ser considerado nesta situação, levando à divisão da série temporal original em três amostras diferentes. Os modelos de previsão foram posteriormente criados através de cada um desses modelos. Os resultados foram expressos através dos três modelos, e como dois deles possuem dados existentes para comparação com dados previstos, foi possível determinar o nível de precisão. No entanto, os modelos não podem ser aplicados imediatamente, uma vez que o impacto do COVID-19 ainda está presente e os voos não voltaram à normalidade. Uma vez resumida essa normalidade, os modelos podem ser aplicados

Reduction of Uncertainty Propagation in the Airport Operations Network

[EN] Airport operations are a complex system involving multiple elements (ground access, landside, airside and airspace), stakeholders (ANS providers, airlines, airport managers, policy makers and ground handling companies) and interrelated processes. To ensure appropriate and safe operation it is necessary to understand these complex relationships and how the effects of potential incidents, failures and delays (due to unexpected events or capacity constraints) may propagate throughout the different stages of the system. An incident may easily ripple through the network and affect the operation of the airport as a whole, making the entire system vulnerable. A holistic view of the processes that also takes all of the parties (and the connections between them) into account would significantly reduce the risks associated with airport operations, while at the same time improving efficiency. Therefore, this paper proposes a framework to integrate all relevant stakeholders and reduce uncertainty in delay propagation, thereby lowering the cause-effect chain probability of the airport system (which is crucial for the operation and development of air transport). Firstly, we developed a model (map) to identify the functional relationships and interdependencies between the different stakeholders and processes that make up the airport operations network. This will act as a conceptual framework. Secondly, we reviewed and characterised the main causes of delay. Finally, we extended the system map to create a probabilistic graphical model, using a Bayesian Network approach and influence diagrams, in order to predict the propagation of unexpected delays across the airport operations network. This will enable us to learn how potential incidents may spread throughout the network creating unreliable, uncertain system states. Policy makers, regulators and airport managers may use this conceptual framework (and the associated indicators) to understand how delays propagate across the airport network, thereby enabling them to reduce system vulnerability, and increase its robustness and efficiency.Rodríguez Sanz, Á.; Gómez Comendador, F.; Arnaldo Valdés, R. (2016). Reduction of Uncertainty Propagation in the Airport Operations Network. En XII Congreso de ingeniería del transporte. 7, 8 y 9 de Junio, Valencia (España). Editorial Universitat Politècnica de València. 36-78. https://doi.org/10.4995/CIT2016.2016.3484OCS367

Uncertainty management at the airport transit view

Air traffic networks, where airports are the nodes that interconnect the entire system, have a time-varying and stochastic nature. An incident in the airport environment may easily propagate through the network and generate system-level effects. This paper analyses the aircraft flow through the Airport Transit View framework, focusing on the airspace/airside integrated operations. In this analysis, we use a dynamic spatial boundary associated with the Extended Terminal Manoeuvring Area concept. Aircraft operations are characterised by different temporal milestones, which arise from the combination of a Business Process Model for the aircraft flow and the Airport Collaborative Decision-Making methodology. Relationships between factors influencing aircraft processes are evaluated to create a probabilistic graphical model, using a Bayesian network approach. This model manages uncertainty and increases predictability, hence improving the system's robustness. The methodology is validated through a case study at the Adolfo Suárez Madrid-Barajas Airport, through the collection of nearly 34,000 turnaround operations. We present several lessons learned regarding delay propagation, time saturation, uncertainty precursors and system recovery. The contribution of the paper is two-fold: it presents a novel methodological approach for tackling uncertainty when linking inbound and outbound flights and it also provides insight on the interdependencies among factors driving performance

Data-aware Soundness Verification and Repair of Data Petri-Nets

openBusiness processes are one of organizations' core assets, impacting directly on the quality of products and services and on the revenue of corporations. A failure in such processes can negatively affect the core of the organization and its production chain. For such reasons, various tools, techniques, and methods have been gathered from different disciplines and collected in what is called Business Process Management (BPM). Petri Net, or Place/Transition (P/T) Net, is one such tool: it is a powerful modeling formalism combining a well-defined mathematical theory with a graphical representation of the dynamic behavior of systems. Given the endless heterogeneity of cases and the extensive combinations between the various resources that interact in a process, additional Petri Net extensions were designed through the years, each aiming to provide more expressive power to describe a broader range of systems. One is Data Petri Net (DPN). This Petri Net-based modeling formalism allows adding a data dimension to the traditional control flow, which permits both the description of how data evolve through the lifecycle of the process and the decisions based on such data. The presence of unreachable activities or steps without the possibility to proceed further falls under the concept of soundness, and its verification has been a central topic for different research activities. The following work hooks into soundness verification and provides an approach to repair Data Petri Nets concerning data and decision perspective. It provides an extensive and accurate description of unsound DPNs that helps the reader understand the base cases and their resolution. Due to the presence of false-positive cases within the existing soundness verification techniques in the literature, this work studies such issues and proposes a patch aimed at the correct identification of these unsound DPNs. The verification and repair techniques rely on the Constraint Graph structure, a finite symbolic abstraction of the possibly infinite traces of a DPN.The algorithms proposed assume that the underlying Petri Net is sound, thus focusing solely on the repair of data that determines the behavior of the net, aiming to restore its soundness. They seek to provide a solution with minimal changes from the original DPN, which helps the process designer verify its correctness and plan further developments and optimizations.Business processes are one of organizations' core assets, impacting directly on the quality of products and services and on the revenue of corporations. A failure in such processes can negatively affect the core of the organization and its production chain. For such reasons, various tools, techniques, and methods have been gathered from different disciplines and collected in what is called Business Process Management (BPM). Petri Net, or Place/Transition (P/T) Net, is one such tool: it is a powerful modeling formalism combining a well-defined mathematical theory with a graphical representation of the dynamic behavior of systems. Given the endless heterogeneity of cases and the extensive combinations between the various resources that interact in a process, additional Petri Net extensions were designed through the years, each aiming to provide more expressive power to describe a broader range of systems. One is Data Petri Net (DPN). This Petri Net-based modeling formalism allows adding a data dimension to the traditional control flow, which permits both the description of how data evolve through the lifecycle of the process and the decisions based on such data. The presence of unreachable activities or steps without the possibility to proceed further falls under the concept of soundness, and its verification has been a central topic for different research activities. The following work hooks into soundness verification and provides an approach to repair Data Petri Nets concerning data and decision perspective. It provides an extensive and accurate description of unsound DPNs that helps the reader understand the base cases and their resolution. Due to the presence of false-positive cases within the existing soundness verification techniques in the literature, this work studies such issues and proposes a patch aimed at the correct identification of these unsound DPNs. The verification and repair techniques rely on the Constraint Graph structure, a finite symbolic abstraction of the possibly infinite traces of a DPN.The algorithms proposed assume that the underlying Petri Net is sound, thus focusing solely on the repair of data that determines the behavior of the net, aiming to restore its soundness. They seek to provide a solution with minimal changes from the original DPN, which helps the process designer verify its correctness and plan further developments and optimizations

Scenario-Driven Development of Service-Oriented Systems

Service-oriented architecture (SOA) is a software architectural style, which relies on reusable and composable services. In addition to software-orientation, SOA includes a business viewpoint, so that business requirements can be captured as high level business processes. Business processes can be implemented, for example, as an orchestration of different service components. Individual services participate in the overall execution of business processes by providing elementary service activities. In addition to flexibility and services reuse, bridging of business and information technology (IT) views is one of the claimed benefits of SOA. Development of service-based systems includes a range of different activities. However, development of service-based systems is still lacking systematic and tool vendor independent practices and development methods. In this thesis, a development process for a service provider, called Service Product Development Process (SPDP), is presented. It consists of several development phases and related activities. The input for SPDP includes high level business process requirements. The result of the process is a new service-based product to be added to the service provider’s product portfolio. The purpose of this thesis is to study the applicability and the benefits of applying a scenario-driven approach, a type of requirement-driven development, for the development of service-based systems. Scenarios are used to capture functional system requirements as simple message sequences given as UML sequence diagrams. The scenario-driven approach is applied to different phases of SPDP including business process development, service specification, and service realization. The proposed scenario-driven approach is not limited to the SPDP context. It is rather a general purpose framework for development of service-based systems or products, called SceDA. SceDA includes three independent scenario-based methods, which are targeted to support different development phases of service-based systems. One of the three methods is used for scenario-based business process development. The other two methods are targeted at service development, in particular, service specification and service realization. Service specification is supported by a method for automatically mining and re-documenting the development rules as scenarios. To support service realization, a method for generating source code for individual service and client applications has been developed. Each method includes a description of the developed tool support and a case study.Case studies are used for constructing and evaluating the three scenario-based methods developed. Each method is applied as a case study in the context of development phases of SPDP. In the first case study, scenario-driven business process development method is applied. Two other case studies concern constructing and using scenarios for application development. One case study utilizes the scenario mining method. In the other case study, the code generation method is applied