Business Process Quality Computation: Computing Non-Functional Requirements to Improve Business Processes

Business processes and information systems mutually affect each other in non-trivial ways. Frequently, the business process design and the information system design are not well aligned. This means that business processes are designed without taking the information system impact into account, and vice versa. Missing alignment at design time often results in quality problems at runtime, such as large response times of information systems, large process execution times, overloaded information systems or interrupted processes. Aligning business process quality and information system quality at design time requires to
\nsolve the following problems (P). Business process quality and information system quality have to be characterized. P1: In contrast to information system quality, which is specified in the ISO/IEC 9126 standard, for example, there is no common and comprehensive understanding of business process quality. P2: Beyond that, current business process
\nmodeling notations do not aim to represent quality aspects. The impact of a business process on the quality of an information system, and vice versa, is unknown at design
\ntime. P3: The mutual impact between business processes and information systems must be predicted at design time.
\nIn this thesis, the Business Process Quality Reference-Model (BPQRM), a quality model for business processes, is introduced. The model allows for a comprehensive characterization of business process quality (P1). The BPQRM is applied successfully in a case study to
\nidentify potential for process quality improvement in practice. Based on the BPQRM an existing process modeling notation is extended by model elements to represent quality
\naspects (P2). Simulation is a powerful means to predict the impact of a business process on the quality of an information system, and vice versa, at design time. This thesis proposes two simulation approaches to predict the mutual impact between business processes and information systems, in terms of performance (P3). The approach Business
\nIT Impact Simulation (BIIS) defines interfaces between the business process simulation and the information system simulation. Performance-relevant information is exchanged
\nvia the interfaces between both simulations. Using business process simulation and information system simulation in isolation, workload burstiness is not adequately reflected.
\nThis is especially true for occasional, volatile peak loads. Workload burstiness can significantly affect the performance of business processes and information systems. The approach Integrated Business IT Impact Simulation (IntBIIS) for the integration of business processes and information systems in a single simulation allows for reflecting workload burstiness correctly. The simulation approaches support the comparison of design alternatives and the verification of a certain design against requirements. A case study confirms the feasibility in practice and the acceptance from practitioners’ point of
\nview.

Companies increasingly adopt process management systems (PrMS), which offer promising perspectives for a more flexible and efficient process execution. However, for many process-aware application systems (e.g., ERP or CRM systems), the underlying process logic is still hard-coded. As a consequence, these business applications are both complex to design and costly to maintain; i.e., they require long development cycles, and even simple process changes might result in costly code adaptions and high efforts for testing. One reason for this situation stems from the fact that contemporary PrMS were primarily designed for the support of highly structured, repetitive business processes. By contrast, many processes found in practice are rather unstructured or semi-structured, i.e., they are knowledge-intensive and driven by user decisions. In addition, the business functions to be integrated with these processes usually cannot be straight-jacketed into activities. For all these reasons, the activity-centered paradigm of contemporary PrMS is by far too inflexible for realizing more advanced business applications. This deficiency mainly stems from the unsatisfactory integration of processes and data in existing PrMS. Despite emerging approaches, which target at a tighter integration of process and data, a unified and comprehensive understanding of the relationships between them is still missing. This thesis first analyzes real processes not adequately supported by existing PrMS and elaborates their characteristic properties. As a major insight it became clear that in many application scenarios comprehensive process support requires both object- and process-awareness. This means, business processes and business data must not be treated independently from each other. Instead, business processes must comply with the underlying data structure. In particular, in accordance to the given data model comprising object types and object relations, the modeling, execution and monitoring of processes must be based on two levels of granularity: object behavior and object interactions. Further, the individual processes, coordinating the behavior of single object instances, must be coordinated with the ones of related object instances. Opposed to these well-defined process support granularity levels, activities must be executable at different levels of granularity. In particular, while a particular user may only want to work on a particular object instance, another one may want to process a number of related object instances in one go. Furthermore, process execution must be accomplished in a data-driven manner; i.e., the progress of a process instance mainly depends on available business objects and on value changes of their attributes. Finally, authorized users must be able to access and manage process-related objects at any point in time. Based on the properties identified, this thesis elaborates major requirements for enabling object-awareness in processes management systems. The major contribution of the thesis is the PHILharmonicFlows framework, which addresses these requirements and enables object-aware process management in a comprehensive manner. In particular, the framework not only provides a new process modeling approach, but also establishes a well-defined operational semantics enabling the automatic and dynamic generation of end-user components for object- and process-aware business applications at run-time (e.g., overview tables and user forms). Overall, a holistic framework integrating data, processes and users offers promising perspectives in order to overcome the numerous limitations of contemporary PrMS. This thesis considers research in this area as fundamental maturation of process management technology.

Over the last few years, we have seen the transformation of the traditional monolithic enterprise, in which all operations were performed in-house, to the extended enterprise, which consists of a network of collaborating entities. Global operations, outsourcing, and increasing specialization have all contributed to this trend. One challenge facing the extended enterprise is how to reconnect the information flows and business processes that were disconnected as the enterprise disaggregated. The emergence of web services, service-oriented architectures, and business process modeling and execution standards are helping to address this challenge. Our contention is that the next phase of evolution is the rise of the intelligent enterprise, which is characterized by being able to adapt quickly to changes in its operating environment. The intelligent enterprise monitors its own business processes and its interactions with customers, partners, suppliers, and collaborators; it understands how this information relates to its business objectives; and it acts to control and optimize its operations to meet its business objectives. Decisions are made quickly and accurately to modify business processes on the fly, dynamically allocate resources, or change business partners (e.g., suppliers, service providers) and partnerships (e.g., establish new service level agreements). This talk will describe challenges in managing the business operations of an intelligent enterprise. While a plethora of tools exist for managing the IT infrastructure (servers, storage, and network resources) of the enterprise, there is little systematic support today for the closed loop management and control of business operations. We will describe technology approaches to intelligent business operations management that we are pursuing at HP Labs., the progress we have made, and some open research questions.

Goal-driven business process analysis application in electricity deregulation

Similarity calculation between Business Process Models (BPM) has an important role in the process of managing BPM repository. One of its uses is to facilitate the searching process of a model in the repository. Similarity calculation between business processes is closely related with semantic string similarity. Semantic string similarity is usually performed by utilizing a lexical database, such as WordNet, to find the semantic meaning of words. The problem in WordNet is that this lexical database contains terms wich have more than one meaning or polysemous. Selecting the wrong meaning will decrease the accuracy of similarity calculation process. In this study, we will try to improve the accuracy of similarity calculation of business processes using Word Sense Disambiguation (WSD). The main purpose is to eliminate the ambiguity of polysemous words before calculating the similarity value. WSD is performed by unsupervised methods based on the value of graph connectivity. Then, we used a lexical database that is focused in the business and industry field. The results from this study is able to achieve higher accuracy of the sense selection process for terms especially terms that are related to business and industrial domains. It will also increase the accuracy of similarity value calculation between the business process models .

In cloud-based systems, business process models compose loosely coupled services to fulfill a certain goal. In order to ensure a high quality of service (QoS) of these systems, irregularities and violations need to be detected and handled at runtime by adapting the system. As a consequence, engineering such systems requires an explicit modeling of adaptation rules, which define how the system is adapted under certain conditions. These rules are defined based on models that specify QoS agreements as well as service bindings and business processes that are adapted. In this paper, we present a modeling approach for adaptive, cloud-based systems which supports the explicit specification of adaptation rules. We are introducing a metamodel for specifying bindings between business processes and cloud services considering Service Level Agreements that define the required QoS. In order to express adaptations of business processes on different levels of granularity, we are using an extended metamodel including fragments that group multiple process elements.

Business Process Models (BPMs) are commonly used in complex business operations. These BPMs are used not only for functional definition of processes but also for their conformance and performance quality evaluations. However, different business domains involve varied operations having multiple stakeholders with different quality requirements. A holistic Quality Evaluation Framework (QEF) is presented to capture and validate these varied quality requirements of such processes using their respective BPMs. The flexible framework consists of a context specific quality model, generic methods and elements to capture quality characteristics in form of profiles in BPMs. The implementation approach of QEF includes use of quality analysis for process quality validation. The case study of a claims settlement process demonstrates the benefits of using proposed QEF.

Process and data are equally important for business process management. Data is especially relevant in the context of automated business processes, and process controlling. In the context of knowledge-intensive domain, data modified by engineers and used by a fully automatic manufacturing system can lead to unpredictable errors. In this paper, a method permitting the discovery of truly enforced business rules used by the process is proposed. These rules will be highlighted using data from the model of the studied process. The proposed methodology is mainly based on a data mining approach. The proposed method has been tested on data from semiconductor industry, in which processes are known to be complex, and the number of business rules is known to be important. The results show that the method is efficient in assisting engineers in process errors detection and practical process improvement.

The increasing adoption of Process-aware Information Systems (PAISs), together with the variability of Business Processes (BPs) across different application contexts, has resulted in large process model repositories with collections of related process model variants. To reduce both costs and occurrence of errors, the explicit management of variability throughout the BP lifecycle becomes crucial. In literature, several proposals dealing with BP variability have been proposed. However, the lack of a method for their systematic comparison makes it difficult to select the most appropriate one meeting current needs best. To close this gap, this work presents an evaluation framework that allows analyzing and comparing the variability support provided by existing proposals developed in the context of BP variability. The framework encompasses a set of language requirements as well as a set of variability support features. While language requirements allow assessing the expressiveness required to explicitly represent variability of different process perspectives, variability support features reflect the tool support required to properly cover such expressiveness. Our evaluation framework has been derived based on an in-depth analysis of several large real-world process scenarios, an extensive literature review, and an analysis of existing PAISs. In this vein, the framework helps to understand BP variability along the BP lifecycle. In addition, it supports PAISs engineers in deciding, which of the existing BP variability proposals meets best their needs.

In the manufacturing industry, the business process of selling roll forming machines plays an important role in producing products with high quality and high efficiency. Therefore, this research was conducted to improve the effectiveness of business processes on Vietsteel Brand Roll Forming Machine customer orders at PT Vinatech using the Business Process Improvement (BPI) method and streamlining techniques. The potential problems identified lie in making approval profile designs that are still done manually, which results in errors in machine design and delays in shipping goods. After improvements were made to business processes through upgrading efforts in the streamlining category, there was a significant decrease in resource usage and accelerated the customer order business process at PT Vinatech. Thus, the results of this research can support the improvement of quality and efficiency of business processes in customer orders of Vietsteel Brand Roll Forming Machine at PT Vinatech which has a positive impact on customer satisfaction and company profitability.

AMFIBIA is a meta-model that formalises the essential aspects and concepts of business processes. Though AMFIBIA is not the first approach to formalising the aspects and concepts of business processes, it is more ambitious in the following respects: Firstly, it is independent from particular modelling formalisms of business processes and it is designed in such a way that any formalism for modelling some aspect of a business process can be plugged into AMFIBIA. Therefore, AMFIBIA is formalism-independent. Secondly, it is not biased toward any aspect of business processes; the different aspects can be considered and modelled independently of each other. Moreover, AMFIBIA is not restricted to a fixed set of aspects; new aspects of business processes can be easily integrated. Thirdly, AMFIBIA does not only name and relate the concepts of business process modelling, as it is typically done in ontologies or architectures for business process modelling. Rather, AMFIBIA also captures the interaction among the different aspects and concepts and therefore fully defines the dynamic behaviour of a business process model, with its different aspects modelled in different notations. To prove this claim, we implemented a prototype of a formalism-independent workflow engine based on AMFIBIA. This workflow engine, also called AMFIBIA, is open for new aspects of business processes and new formalisms can be easily integrated. In this paper, we present the concepts of AMFIBIA and discuss the principles and concepts of its design.

The COVID19 pandemic has indirectly changed the landscape of the business environment system through cloud intelligence within the digital ecosystem that has as a goal increasing the access, efficiency, effectiveness, equity and quality of business processes through cloud intelligent systems. Cloud intelligent systems are becoming revolutionary in today’s world pandemic causing a complete and drastic change to a variety of industries, including, security, transportation, business, logistics and manufacturing. The main purpose of cloud intelligence systems is to facilitate the ease of access from any location and the management of practical computing resources. One of the challenges faced by cloud technology today is scheduling. The role of scheduling algorithms is very important, since tasks are executed by orders that may need more attention. Here, scheduling algorithms intended to minimize monetary cost and minimize makespan time to execute the workflow are presented. This study proposes cloud intelligent systems apps through an approach to cloud computing scheduling that may lead to great benefits and efficiency. The result is very promising. It showed that there are numerous applications of intelligent systems due to the more advanced hardware being built nowadays, plus business processes advancing to become smarter and more efficient in growing profitably over a destructive digital ecosystem during the COVID19 pandemic. The results indicate that intelligent systems over the cloud play a big role not just for interacting with the world helping businesses grow, but as well as in the advancement for a better tomorrow.

PT. Electrical MBS address at the Rukan City Garden Maisonete A 1/5 East Cengkareng, West Jakarta is a PT engaged in the sale of electrical equipment that is being developed in the field of buying and selling daily necessities. The author conducted research based on the company's business processes. Managed business process is ordering, purchasing and sales. Research conducted covering all business processes that originally done manually later on Automated via a web-based application system. The author also help the company to see the reports generated by the existing business processes. Moreover, the author also assist the company in determining the supplier for each item that is using the Decision Support System with Analytical Hierarchy Process method. Aplication made is expected to help the company to run its business and simplify the control of the company in general .

Business process modeling (BPM) is one of the key technologies to benefit enterprises with higher efficiencies and greater business values. However, BPM requires intensive business expertise and human resources. Thus, it is valuable and challenging to enable fast delivery of reusable business process designs, regarding the existence of various popular business processes modeling languages and fast changing markets. In this paper, we generate language-specific business process models and process interaction semantics from UML 2.0 process models. A WS-BPEL metadata model and a process interaction semantics metadata model is defined to annotate UML 2.0 business process model as stereotypes; with a set of transformation patterns, we can generate a WS-BPEL business process model and a process interaction semantics file from each annotated UML 2.0 process model. Our approach can also be similarly applied to other process modeling languages to highly reuse the business process model in UML 2.0.

Formulation of the problem. In the conditions of global competition, lean production acquires special importance. For enterprises all over the world, the only way to survive in the market is to produce goods and provide services that most fully satisfy the demands of consumers, while using advanced management methods and technologies. Lean manufacturing is one of the modern tools of production organization and management technology, which is used to improve the quality of products and services, the most complete satisfaction of consumer needs, while ensuring a careful attitude to the company's resources and their savings.
 The purpose of the study is the further development of methodological, methodical and practical approaches to the concept of Lean manufacturing to improve the quality of the enterprise's business processes.
 Research methods. The research used scientific methods, such as theoretical generalization, comparison, analysis, synthesis.
 Result. In the process of research, a comparison of traditional business management and the concept of lean production was made and revealed. that the concept of lean production has such advantages as the transition from centralized, vertical management to horizontal, involvement of all employees in the process, teamwork, focus on rational use of resources. The concept of lean production is aimed at eliminating the following main types of losses: overproduction of goods; waiting for raw materials, semi-finished products, necessary service information; unnecessary movement of materials; redundant processing steps arising due to errors in the design of business processes; excessive stocks and business processes leading to their occurrence; unjustified rotation of personnel in the work process; production of waste; underutilization of employees' creative potential.
 Conclusions. Six main elements and 52 components (requirements) of Lean manufacturing are defined based on the SAE J4000 standard for more successful application of lean manufacturing ideas in practice production to analyze the levels of implementation of lean manufacturing methodology components and elements. The main elements of the concept of lean manufacturing, the development and improvement of which should be focused on, are: company management and trust in it; enterprise personnel; information environment; chain "supplier – organization – consumer"; product; business processes. An important role in the concept of lean manufacturing is played by the 5S ordering system and the system of general maintenance of TPM equipment .
 Keywords: lean manufacturing; losses; flow of value creation; 5S ordering system; system of general maintenance of TPM equipment; SAE standard J4000.