Daniel Metz

Towards an IT-Framework for Digital Enterprise Integration

Globalization has resulted in a dynamic environment which is a combination of uncertainties and unpredictable behaviour of customers, enterprise partners and market conditions. As a consequence, manufacturing enterprises tend to improve the monitoring and control of enterprise value creation processes to achieve flexibility and adaptability. Enterprise integration (EI) can be seen as a prerequisite for realizing a multi-loop control system within and across different enterprise levels. Various standards are available for EI but these standards do not mention how to realize them in terms of technology. Therefore, an IT-framework for digital EI based on different standards and technologies is proposed. This IT-framework describes integration of manufacturing level and enterprise control level, graphical user interface for visualization and control, and process control using workflow management system and rule-based system. Finally, a case study is presented showing the application of the IT-framework for different types of manufacturing.

An event driven software framework for enabling enterprise integration and control of enterprise processes

In recent years to sustain competitive advantages, manufacturing enterprises strive for improvements in their monitoring and control of enterprise processes. Hence in the current contribution, an event driven software framework for enabling enterprise integration (EI) and enhancing control of enterprise processes is presented. The proposed framework is composed of four main components: First, a data collection engine is used for physical resource integration. Second, data aggregation engine integrates data from different enterprise levels, thus enabling EI. Third, control of enterprise processes is performed using a complex event processing engine. Finally, real-time resource and control data, and historical data can be visualized through process visualization clients. The framework has been validated in an industrial scenario.

Cost estimation of automotive sheet metal components using knowledge-based engineering and case-based reasoning

Responding quickly to a customers request with a sufficiently precise offer is one of the challenges faced by almost every manufacturing enterprise. Currently, necessary information is passed from department to department and in many cases this information is waiting to be processed. Further, number of offers that are converted into orders is small making the process of preparing an offer relatively costly. Research has been carried out to automatically determine process plans and estimate cost of simple sheet metal components. Unfortunately, this research has not been extended to simultaneously determine process plan and cost of complex deep drawn components. To overcome these drawbacks and to substantially improve the efficiency and precision of the time consuming process of offer preparation, a new methodology is presented which utilizes knowledge-based engineering and case-based reasoning. Inputs obtained to create an offer can be used to generate basic tool structure for the downstream processes.

Online Monitoring and Control of Enterprise Processes in Manufacturing Based on an Event-Driven Architecture

Manufacturing enterprises strive for improvements in their monitoring and control of enterprise processes (i.e., business and manufacturing processes) with intention to sustain competitive advantages, and achieve higher degree of flexibility and adaptability of enterprise processes. Hence in the current contribution, a framework based on event driven architecture is elaborated which can be employed to realize enterprise integration, and enhance online monitoring and control of enterprise processes. A process model is been presented that assists the introduction, configuration and implementation of the envisaged framework. The framework is composed of following components: data collection engine, data aggregation engine, process database, complex event processing engine, and process visualization clients. Finally, the framework has been validated in an industrial scenario.

Proactive control of manufacturing processes using historical data

Todays enterprises have complex manufacturing processes with several automation systems. These systems generate enormous amount of data in real-time representing feedbacks, positions, and alerts, among others. This data can be stored in relational databases as historical data which can be used for product tracking and genealogy, and so forth. However, historical data is not been utilized to proactively control the manufacturing processes. The current contribution proposes a novel methodology to overcome the aforementioned drawback. The methodology encompasses three process steps. First, offline identification of critical control-related parameters of manufacturing processes and defining a case base utilizing previously identified process parameters. Second, update the case base with real-time data acquired from automation systems during execution of manufacturing processes. Finally, employ similarity search algorithms to retrieve similar cases from the case base and adapt the retrieved cases to control the manufacturing processes proactively. The proposed methodology is validated to proactively control the manufacturing process of a molding machine.

Identification and Assimilation of Knowledge for Real-Time Control of Enterprise Processes in Manufacturing

Today’s enterprises are operating in a complex and volatile business environment. To address this situation, enterprises try to realize horizontal and vertical integration of business and engineering processes leading to real-time enterprise. Enterprise data model assists in integrating data generated from automation systems in (milli) seconds and data from business applications referring to long time horizons (e.g., days). However, the integrated data is not used extensively for real-time control of enterprise processes. Therefore, a methodology is presented for identification and assimilation of knowledge for real-time control of enterprise processes. Real-time control of enterprise processes aims at increasing performances in manufacturing.

Towards an Integrated Virtual Value Creation Chain in Sheet Metal Forming

OEMs are focusing more on manufacturing critical components whereas non-critical components are outsourced to suppliers. At supplier’s side, production planning process is intervened between sales and production processes. Past experiences can be adapted to support production planning activities. Hence, it is crucial to identify knowledge from previously solved cases on demand and assimilate it. At the Information Systems Institute, various methodologies (e.g., similarity search in product and process data) are developed to support aforesaid knowledge intensive activities in sheet metal forming. However, these methodologies are used as stand-alone applications. Therefore, the current contribution introduces an integrated virtual value creation chain in sheet metal forming which utilizes previously developed methodologies. Also, these methodologies are elaborated as part of the integrated virtual value creation chain. The developed methodologies are heterogeneous and are coupled through a shared knowledge base.

Real-time enterprise — schnelles handeln für produzierende unternehmen

ZusammenfassungDie Vision des Echtzeitunternehmens — englisch Real-Time Enterprise (RTE) — kann auch für produzierende Unternehmen Realität werden. Neben den Einflussfaktoren Qualität und Kosten werden zunehmend Zeit und Innovationsfähigkeit zu entscheidenden Erfolgsfaktoren im globalen Wettbewerb. Die schnelle und adäquate Reaktion auf Ereignisse in wertschöpfenden Unternehmensprozessen gewinnt an Bedeutung. Welche Konzepte sollten bei der Etablierung eines RTE für produzierende Unternehmen berücksichtigt werden?

About adopting event processing in manufacturing

Manufacturing enterprises strive for improvements in their monitoring and control of enterprise processes to sustain competitive advantages. In this context, enterprise integration (EI) across various enterprise levels and event processing are indispensable. However in reality, enabling EI and employing event processing for online monitoring and control of enterprise processes are elusive goals for many of the manufacturing enterprises. In the contribution, a framework for enabling EI is elaborated, which can be considered as a building block towards realizing the aforementioned goals. The framework encompasses various components: data collection engine, data aggregation engine, event processing engine, performance measurement, and offline analysis. This framework can be exploited in enhancing online monitoring and control of enterprise processes by employing event processing. The framework has been implemented and validated in an industrial scenario.

Event-Driven Framework for Real-Time Enterprise

The previous discussion on the realization of RTE for manufacturing enterprises– also considering managerial, engineering and computer science perspectives–reveals the urgent need for (i) vertical integration of various enterprise levels (i.e., from shop floor to top floor); and (ii) realization of multiple control loops between these enterprise levels. Consequently, the aim of the presented research work is the development of an IT-framework for real-time monitoring and control of manufacturing processes. Thereby, previous achievements that have been made by management, engineering and computer science communities are incorporated.