Frederick Y. Wu

Modeling business contexture and behavior using business artifacts

Traditional process modeling approaches focus on the activities needed to achieve a business goal. However, these approaches often pose obstacles in consolidating processes across an organization because they fail to capture the informational structure pertinent to the business context or contexture. In this paper, we discuss business artifact-centered operational modeling. Artifacts capture the contexture of a business and operational models describe how a business goal is achieved by acting upon the business artifact. Business artifacts, such as Purchase Order or Insurance Claim, provide business analysts an additional dimension to model their business. With operational models, they can describe how a business operates by processing business artifacts and adding business value to the artifacts. This approach has been successfully employed in a variety of customer engagements. We summarize our best practices by describing nine operational patterns. Furthermore, we develop a computational model for operational models based on Petri Nets to enable formal analysis and verification thereof.

On the Duality of Information-Centric and Activity-Centric Models of Business Processes

Most of the work in modeling business processes is activity-centric. Recently, an information-centric approach to business process modeling has emerged, where a business process is modeled as the interacting life cycles of information entities. The benefits of this approach are documented in a number of case studies. The goal of this paper is to formalize the information-centric approach and derive the relationships between the two approaches. We do this by formally defining the notion of a business entity from first principles and using this definition to derive an algorithm that generates an information-centric process model from an activity-centric model. We illustrate the two models using a real-world business process and provide an analysis of the respective strengths and weaknesses of the two modeling approaches.

Automatic defect classification for semiconductor manufacturing

Abstract.Visual defect inspection and classification are important parts of most manufacturing processes in the semiconductor and electronics industries. Defect classification provides relevant information to correct process problems, thereby enhancing the yield and quality of the product. This paper describes an automated defect classification (ADC) system that classifies defects on semiconductor chips at various manufacturing steps. The ADC system uses a golden template method for defect re-detection, and measures several features of the defect, such as size, shape, location and color. A rule-based system classifies the defects into pre-defined categories that are learnt from training samples. The system has been deployed in the IBM Burlington 16 M DRAM manufacturing line for more than a year. The system has examined over 100 000 defects, and has met the design criteria of over 80% classification rate and 80% classification accuracy. Issues involving system design tradeoff, implementation, performance, and deployment are closely examined.

A-Teams: An Agent Architecture for Optimization and Decision Support

The effectiveness of an agent architecture is measured by its successful application to real problems. In this paper, we describe an agent architecture, A-Teams, that we have successfully used to develop real-world optimization and decision support applications. In an A-Team, an asynchronous team of agents shares a population of solutions and evolves an optimized set of solutions. Each agent embodies its own algorithm for creating, improving or eliminating a solution. Through sharing of the population of solutions, cooperative behavior between agents emerges and tends to result in better solutions than any one agent could produce. Since agents in an A-Team are autonomous and asynchronous, the architecture is both scalable and robust. In order to make the architecture easier to use and more widely available, we have developed an A-Team class library that provides a foundation for creating A-Team based decision-support systems.

Artifact-Based Transformation of IBM Global Financing

IBM Global Financing (IGF) is transforming its business using the Business Artifact Method, an innovative business process modeling technique that identifies key business artifacts and traces their life cycles as they are processed by the business. IGF is a complex, global business operation with many business design challenges. The Business Artifact Method is a fundamental shift in how to conceptualize, design and implement business operations. The Business Artifact Method was extended to solve the problem of designing a global standard for a complex, end-to-end process while supporting local geographic variations. Prior to employing the Business Artifact method, process decomposition, Lean and Six Sigma methods were each employed on different parts of the financing operation. Although they provided critical input to the final operational model, they proved insufficient for designing a complete, integrated, standard operation. The artifact method resulted in a business operations model that was at the right level of granularity for the problem at hand. A fully functional rapid prototype was created early in the engagement, which facilitated an improved understanding of the redesigned operations model. The resulting business operations model is being used as the basis for all aspects of business transformation in IBM Global Financing.

An Agent-Based Approach for Scheduling Multiple Machines

We present a new agent-based solution approach for the problem of scheduling multiple non-identical machines in the face of sequence dependent setups, job machine restrictions, batch size preferences, fixed costs of assigning jobs to machines and downstream considerations. We consider multiple objectives such as minimizing (weighted) earliness and tardiness, and minimizing job-machine assignment costs. We use an agent-based architecture called Asynchronous Team (A-Team), in which each agent encapsulates a different problem solving strategy and agents cooperate by exchanging results. Computational experiments on large instances of real-world scheduling problems show that the results obtained by this approach are significantly better than any single algorithm or the scheduler alone. This approach has been successfully implemented in an industrial scheduling system.

A model-driven transformation method

Model-driven architectures (MDA) separate the business or application logic from the underlying platform technology and represent this logic with precise semantic models. These models are supposed to span the entire life cycle of a software system and ease the software production and maintenance tasks. Consequently, tools will be needed that support these tasks. In this paper, we present a method that implements model-driven transformations between particular platform-independent (business view) and platform-specific (IT architectural) models. On the business level, we focus on business view models expressed in ADF or UML2, whereas on the IT architecture side we focus on service-oriented architectures with Web service interfaces and processes specified in business process protocol languages such as BPEL4WS.

Cooperative Multiobjective Decision Support for the Paper Industry

We built and deployed a decision-support system for scheduling paper manufacturing and distribution, an extremely complex task with multiple stages of production and strong interaction between stages. In contrast to earlier approaches, our system considers multiple scheduling objectives and multiple stages of production and distribution simultaneously using multiple evaluation criteria. Our system functions as an intelligent assistant to the schedulers and generates multiple good scheduling alternatives using a portfolio of algorithms and direct human-expert input. The successful deployment of our system at several paper mills in North America has resulted insignificant savings, greater customer satisfaction, and improved business processes.

Core business architecture for a service-oriented enterprise

The business architecture of a service-oriented enterprise can be adequately represented through five main architectural domains: business value, structure, behavior, policy, and performance. In this paper we focus on the core business architecture, the set of essential elements in each of the five domains, and the interrelationships among these elements. The business architecture described in this paper identifies the key elements required for business reasoning and for its application to business transformation through service-oriented solutions. A business scenario involving a fictional company in the apparel business illustrates the concepts presented here.

Scheduling Solutions for the Paper Industry

This paper describes a decision support system for paper production scheduling. This is the first system to provide an integrated solution to paper production scheduling and to consider interactions between different stages of the manufacturing and distribution process. Using a multicriteria optimization approach, the system generates multiple enterprisewide schedules to reveal tradeoffs between the multiple, often competing, objectives. The large portfolio of algorithms used by the system is embedded in an agent-based decision support framework, called Asynchronous Team (A-Team). Successful implementations of the system in several paper mills in North America have resulted in significant savings and improved customer satisfaction.