A process insight repository supporting process optimization

Recently domestic manufacturing companies have been experiencing worsening profitability and stunted growth due to the long-term economic recession and the rapid rise of developing countries such as China and Southeast Asia. These difficulties force many companies to concentrate their core competencies on new value creation and innovation in order to gain momentum for new growth. Enterprise Resource Planning (ERP) has been considered as one of viable solutions. Among the various modules in ERP, shop floor control function in the production management module is rather limited. In order to overcome this problem, Manufacturing Execution System (MES) has been used as a subsystem which has a strong information gathering power and flexibility. Both systems interact closely with each other. In particular, ERP requires fast, accurate shop floor information at MES. This paper describes how to synchronize relevant information between ERP and MES with theory of constraints (TOC). The processing time information transmitted from the MES workplace is received at the ERP workplace. In the process, the received processing time is causing information distortion in ERP, when the information gathering standard of MES is different from the ERP information interpretation standard. The Drum-Buffer-Rope theory of TOC was applied to resolve this problem, therefore, information synchronization between both systems was made. As a precondition, the standard time of the upper ERP system was rearranged according to the capacity constraints resource. As a result, standard time restructuring has affected changes in labor costs. Standard labor costs have come close to actual ones, and information synchronization of MES transmission data has improved the reliability of standard product costs, such that it enabled various company-wide restructuring actions to be much more effective.

In this paper, the system integration of an Advanced Planning and Scheduling (APS) system with Enterprise Resource Planning (ERP) and Manufacturing Execution System (MES) for a Semiconductor Backend Assembly environment is described. The company is one of the worldwide market leaders in semiconductor packaging technology. SIMTech was responsible for the implementation of the Planning & Scheduling functions through its APS application which is called Gintic Scheduling System (GSS). GSS system has been integrated with the other two key manufacturing software systems, namely ERP and MES, with the CIM framework. This paper emphasizes the system integration between the GSS and the customer's existing ERP and MES systems. The paper starts with a broader overview of the APS, ERP and MES systems with the focus on the linkage of APS with ERP and APS with MES. It then introduces the brief background information of the implementation and the integration methodology. Detailed work of the integration is laid out in the fond of integration model structure and illustrated by the system integration mechanism. Various data types that need to be integrated are also elaborated. Further discussions continue with the practical implementation issue like the required frequency of data integration and also the two approaches of data transfer. Finally the paper shares the experiences and lessons the team has learned through the implementation process and concludes the essence of the system integration work.

Towards improving detection of early warning signals within organizations : an approach to the identification and utilization of underlying factors from an organizational perspective

Enterprise resource planning (ERP) in gastronomy education

With the further integration of the informatization and industrialization, it is a key factor for enterprise to develop them by enterprise information construction. At present, with the development of computer, enterprise informatization generally has formed three layers architecture, which contains: ERP (Enterprise Resource Planning), MES (Manufacturing Execution System) and PCS (Process Control System). MES plays an irreplaceable position in the enterprise informatization. However, different needs of the design for these systems. Then, they lead system not to share information, business process effectively and work together with others. Then finally lead to "Information Island". It has made people to pay more attention to the topic, which is how to implement the exchange of information real-time and accurately between ERP, PCS and MES. So, we analyze some major exchange ways of the present information between MES and other systems in this paper. Then, we propose a flexible and configurable EAI architecture-AiOintegration (All-in-One integration), which has integrated the current methods of exchanging between system information. And AiOintegration implemented information exchange of cross-language and cross-platform between with MES and other systems.

This paper investigates the deployment of Manufacturing Execution Systems (MES) within SAP environments in manufacturing enterprises. Through an extensive literature review, it examines the critical aspects of integrating MES with SAP Enterprise Resource Planning (ERP) systems, encompassing implementation strategies, benefits, challenges, and best practices. The study underscores the significance of real-time data integration between MES and SAP for enhanced decision-making and resource utilization. It further highlights the role of MES in facilitating lean manufacturing principles and the essential nature of change management in implementation projects. The findings emphasize the necessity of aligning MES implementation with overarching business objectives and maintaining continuous performance monitoring. Practical implications for manufacturers contemplating MES implementation in SAP environments are discussed, including the importance of strategic planning, robust data integration, employee training, and ongoing system optimization. The paper concludes by identifying areas for future research, such as the impact of emerging technologies on MES implementation. Keywords: Manufacturing Execution Systems (MES), SAP, Enterprise Resource Planning (ERP),Manufacturing enterprises, System integration, Real-time data, Lean manufacturing, Change management, Implementation strategies, Performance monitoring, Data integration, Employee training, System optimization, Emerging technologies

University of Edinburgh, School of Informatics, EH8 9AB, Edinburgh, Scotland, United Kingdom ; cristinutza0107@yahoo.com Abstract. This paper discusses the problem of multidimensional databases, with the purpose of demonstrating the efficient support offered by them for the management of OLAP processing and motivation of decisions, especially the ones related to environmental risks. The OLAP (On-Line Analytical Processing) systems that implement or use multidimensional databases are oriented towards decision makers and allow them to an easily process, sectioning and grouping of data, as well as the visualization of data from different perspectives, for the discovery of the factors that would influence a certain behavior. OLAP systems offer advanced statistical analysis facilities, such as the one based on time series or forecasts, which are based on predefined models. The calculation of the environmental risk offers an image of the degree of air pollution due to specific polluting factors, obtained especially as result of the industrial processes that have taken place in the Targoviste, in Dambovita area. An OLAP system, consisting of decision support components, was implemented as part of the PN2 three years research project: “Sustainable Management System of Resources Used for Monitoring and Evaluating the Environmental Risks in Order to Prevent the Negative Effects and to Manage Crises Situations - MEMDUR”, code D11-037/18.09.2007. Keywords: environmental risks, multidimensional databases, OLAP systems, SOLAP architecture, MEMDUR project.

The automatic detection of divergences from a desired process behavior is a common research topic in the business process management community. An established technique to analyze processes is called conformance checking. Given a definition of a process in form of a process model, conformance checking can be used to test whether the executions of a process contained in a so-called event log data structure are conforming with the process as it was defined. The result is a comparison of the execution traces and their respective correct execution, according to the process model. This technique provides insights into where the divergence has occurred and how the execution must be altered to conform to the process model. However, a problem is that it requires a process model to be available. Process models in the correct format are not always available. Contrary to conformance checking, process anomaly detection aims to find anomalous executions without relying on a predefined process model. A process anomaly detection algorithm derives the process logic from the event log itself and exploits the patterns found within the event log to distinguish normal from anomalous process executions. Though process anomaly detection provides the benefit of not relying on a process model, it typically does not provide the level of detail that conformance checking does. A process execution can either be normal or it can be anomalous. This dissertation proposes process anomaly correction, a novel approach that combines the benefits of conformance checking and process anomaly detection. Given only an event log, process anomaly correction detects anomalous executions, clearly indicates where the anomaly has occurred during the execution and suggests possible corrective measures. The solution presented in this work is based on a new concept to the field of process anomaly detection: Process learning. In process learning, the task of understanding the process based on the example data is transformed into a learning problem in which a neural network is trained to predict the very next activity in a running process execution. The resulting machine learning model thus represents an approximation of the real process that created the data. This cumulative dissertation consists of five contributions to the field of business process management that demonstrate how, starting from a process anomaly detection, process anomaly correction is achieved in a series of four steps. (1) Process learning is employed to generate an approximated model of the process logic. (2) The limitation of only distinguishing between normal and anomalous process executions is overcome by employing the process learning model which processes the process executions on a finer level of detail than existing approaches. (3) The necessity of providing manual threshold settings, as it is typical for process anomaly detection algorithms, is replaced by an automatic parameterization utilizing the process learning model. (4) The predictive capabilities of the process learning model are exploited to generate possible corrections of detected anomalies. The resulting process anomaly correction approach can be employed in scenarios where classic conformance checking would be infeasible, due to the restriction of relying on a process model. Furthermore, it can be employed alongside classical conformance checking, for it incorporates more information coming from the event log than classical conformance checking (such as employees executing a process step, in which country the process is executed, etc.), and thus provides a new perspective for the process analyst.

ERP systems are information systems that support the integration of value-added processes of enterprises. Based on the concept of modular structures, n-tier client/server architecture and centralized databases, numerous ERP systems have been developed in the market. The vast number of ERP products available has given users the chances to select suitable products for implementation. However, the lack of evaluation framework has made the selection process difficult. In this paper, a framework for analyzing and distinguishing ERP systems based on IT attributes is proposed. This design of the framework is based on client/server architecture, browser based computing, system integration standards and business enabling features. The framework includes 61 attributes and thus allows it to differentiate large number of software. Major ERP systems sold in the greater China area are evaluated with the framework to evaluate the discriminating capability of the framework. The result implies that the framework can reasonably discriminate major ERP systems.

This paper analyzes the cases where the hotels have increased their services and enhanced their work process through IT solutions to cope with computerization globalization. Also the cases have been studies where national hotels use the CRM solution internally to respond effectively to customers requests, increase customer analysis, and build marketing strategies. In particular, this study discusses the introduction of the CRM solutions and CRM sales business and marketing services using a process for utilizing the presumed, CRM by introducing effective DEA(Data Envelopment Analysis). First, the comparison has done regarding the relative efficiency of L Company with the CCR model, then compared L Company's restaurants and facilities' effectiveness through BCC model. L Company reached a conclusion that it is important to precisely create and manage sales data which are the preliminary data for CRM, and for that reason it made it possible to save sales data generated by POS system on each sales performance database. In order to do that, it newly established Oracle POS system and LORIS POS system concerned with restaurants for food and beverage as well as rooms, and made it possible to stably generate and manage sales data and manage. Moreover, it set up a composite database to control comprehensively the results of work processes during a specific period by collecting customer registration information and made it possible to systematically control the information on sales performances. By establishing a system which unifies database and managing it comprehensively, impeccability of data has been greatly enhanced and a problem which generated asymmetric data could be thoroughly solved. Using data accumulated on the comprehensive database, sales data can be analyzed, categorized, classified through data mining engine imbedded in Polaris CRM and the results can be organized on data mart to provide them in the form of CRM application data. By transforming original sales data into forms which are easy to handle and saving them on data mart separately, it enabled acquiring well-organized data with ease when engaging in various marketing operations, holding a morning meeting and working on decision-making. By using summarized data at data mart, it was possible to process marketing operations such as telemarketing, direct mailing, internet marketing service and service product developments for perceived customers; moreover, information on customer perceptions which is one of CRM's end-products could feed back into the comprehensive database. This research was undertaken to find out how effectively CRM has been employed by comparing and analyzing the management performance of each enterprise site and store after introducing CRM to Hotel enterprises using DEA technique. According to the research results, efficiency evaluation for each site was calculated through input and output factors to find out comparative CRM system usage efficiency of L's Company four sites; moreover, with regard to stores, the sizes of workforce and budget application show a huge difference and so does the each store efficiency. Furthermore, by using the DEA technique, it could assess which sites have comparatively high efficiency and which don't by comparing and evaluating hotel enterprises IT project outcomes such as CRM introduction using the CCR model for each site of the related enterprises. By using the BCC model, it could comparatively evaluate the outcome of CRM usage at each store of A site, which is representative of L Company, and as a result, it could figure out which stores maintain high efficiency in using CRM and which don't. It analyzed the cases of CRM introduction at L Company, which is a hotel enterprise, and precisely evaluated them through DEA. L Company analyzed the customer analysis system by introducing CRM and achieved to provide customers identified through client analysis data with one to one tailored services. Moreover, it could come up with a plan to differentiate the service for customers who revisit by assessing customer discernment rate. As tasks to be solved in the future, it is required to do research on the process analysis which can lead to a specific outcome such as increased sales volumes by carrying on test marketing, target marketing using CRM. Furthermore, it is also necessary to do research on efficiency evaluation in accordance with linkages between other IT solutions such as ERP and CRM system.

With the development of information technology, information visualization and integration of ERP (Enterprise Resources Planning) and MES (Manufacturing Execution System) are becoming important tasks that many enterprises have to face. The essentiality of product information integration and information visualization was elaborated. Key technologies of the system were studied, such as database integration technologies, information parallelism, data mining and information visualization. The system of production management integration and decision information visualization was developed based on the key technologies. The results show that the production process can be controlled more precisely and the efficiency of production can be improved by this system, and it also provides supports to workshop manager’s production decision.

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.

This paper describes the continuous application of simulation from system design to system operation including the integration of the simulation in a manufacturing execution system (MES). This is done using the example of a real-world manufacturing system, a complex flexible laser welding facility. The results of a simulation study during system design are presented and it is derived how these results strengthened the decision to implement a simulation-based MES. Some technical details of the connection between the Enterprise Resource Planning (ERP) system, the MES, and the Programmable Logic Control (PLC) are explained, as well as the usage of the MES and the simulation by the operations planners (dispatchers).

The deployment of additive manufacturing (AM) processes had a rapid and broad increase in the last years, and the same trend is expected to hold in the near future. A way to better exploit the advantages of such technology is the use of appropriate information tools. However, today there is a lack of software applications devoted to this innovative manufacturing process. To overcome this issue, in the present work the application of manufacturing execution systems (MES), a tool commonly used in traditional manufacturing processes, is extended to AM. Furthermore, a framework for the deployment of shop-floor data, acquired through a monitoring system, in the design phase is presented: hence, MES should cooperate with design for additive manufacturing (DFAM), a set of methods and tools helpful to design a product and its manufacturing process taking into account AM specificities from the early design stages. In order to better understand the advantages of such cooperation, a case study for a proof of concept has been developed: the obtained results are promising, thus an online implementation would be recommended.

In the current era, information technology has boosted every field of life either business industry or healthcare to integrate the internal processes of it. Due to the demand of managing huge data related to these fields numerous information systems play different roles in making the organizational processes robust and up to date. This paper discusses the integrated business intelligence implication specifically for healthcare to provide the fast and precise information on time. Therefore, this paper discusses the idea of building intelligent system based on Enterprise Resource Planning (ERP) databases using exclusively for dermatology diseases by applying data mining techniques. Firstly, classification mining has been applied for categorization data based on patient’s record. Then rules and patterns generated from the categorized data related to dermatology diseases, symptoms and treatments. The proposed system will retrieve the corresponding information related to the given symptoms along with medication and complete treatment. This research aims to integrate different ERP processes with centralized ERP database to provide business intelligence effectively for the dermatologists. The paper has provided with the comprehensive conceptual framework and each step has been discussed in detail.