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1

Manufacturing projects cash-flow dynamics and risk management

Kramarenko S., Shevtshenko E., Karaulova T., Wang Y.

Journal of Machine Engineering

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2009

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Vol. 9, No. 1

91--102

EN

A project portfolio is referred to as an optimal combination of specified projects to best achieve defined goals of an enterprise. The goals may imply either economic and business strategies, or technical strategies. This paper presents an idea of project portfolio management in intelligent decision support systems (IDSS), which emphasizes on the problem of resource allocation, in particular cash. A rational way of distributing cash among different projects is modeled. We propose a concept of cash-flow dynamics module, which can be plugged into IDSS. The IDSS allows project managers to make decisions regarding the order of priority for projects' launching times based on risk and profitability of projects. This paper describes how this module can support cash-flow management processes, from budgeting for future periods to tracking real-time cash flow. Based on an analogy between cash-flow processes and physical flow of fluid, a cash-flow dynamics model is introduced. The theory of Bernoulli principle for cash-flow planning and tracking is applied.

2

Fractal management approach for the manufacturing projects in the collaborative networks of SME-s

Polyantchikov I., Shevtshenko E., Kramarenko S.

Journal of Machine Engineering

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2009

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Vol. 9, No. 4

81--93

EN

Nowadays an increasing number of enterprises realize the importance of competitiveness improvement through collaboration. It is obvious that the collaborative network is becoming an effective tool that enables small and medium sized enterprises (SMEs) to survive under the global crisis pressure. It enforces enterprises to focus resources and means on the main activities, and to rebuild the architecture for manufacturing system in effective ways. Therefore, we decided to continue working on research topic of collaborative manufacturing projects management. In this paper we introduce the novel framework for the further development of the existing collaborative network concept in which we combined multiple project management methodology and fractal model of collaborative network of enterprises. The proposed framework enables SME-s to use resources more efficiently, reduce manufacturing costs, rapidly respond to customer demand changes, increase the productivity, reduce total lead time of collaborative projects, improve the products quality, improve the practice of collaboration in multi-project management, improve stability, share the expensive costs and equipment, reduce inventory, raise the accuracy of the forecast, reduce the data entry time, and improve the performance of delivery. In this paper, we will present the project-based fractal collaborative network framework, multiple project management and fractal model framework. We will introduce our vision of information and communication processes in the novel collaborative network, tasks and relationships of collaborative enterprises project managers, external and internal relationships of project managers.

3

Manufacturing project management in the conglomerate enterprises supported by IDSS

Shevtshenko E., Karaulova T., Kramarenko S., Wang Y.

Journal of Achievements in Materials and Manufacturing Engineering

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2009

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Vol. 33, nr 1

94-102

EN

Purpose: of this paper is to summarize the application study of a general framework of intelligent decision support system (IDSS) to collaborative projects in conglomerate enterprises. In some situations, even with the knowledge of how to find right information and which decision making methods to apply, we do not have enough time to make right decisions at the right time. In this paper, the framework of an IDSS system to support real-time collaboration and enable seamless data exchange is presented. Design/methodology/approach: The important roles of facilitation and organization that the IDSS plays are demonstrated. In the case study, examples of manufacturing projects analysis are given with the known methods, including Analytical Hierarchy Process and Bayes’ rule. Findings: It is demonstrated that IDSS systems can help us to manage information flow, clean data, transform data into knowledge, perform analysis and monitor the effectiveness of manufacturing projects during the whole life cycle. Research limitations/implications: The functionality of the developed framework is limited by the willingness of management style and culture changes in companies, as well as the level of interoperability between commercial software components. Only the essential components that influence the success of the manufacturing projects are considered. Practical implications: Project engineers and managers need to adapt to the new IT-based working environment. Originality/value: New information management model and the framework of IDSS system are proposed. The new collaborative decision making system consists of different parts: management of information flow, preparation of data for decision making, and actual decision making and monitoring of manufacturing projects supported by several methods.

4

Decision analysis in project management process

Kramarenko S., Shevtshenko E., Karaulova T., Wang Y.

Journal of Machine Engineering

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2008

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Vol. 8, No. 1

104--113

EN

Very often we complain about the decisions that were previously made. Yet the fact is that the decisions made were based on the knowledge we had before. By now we have gained more knowledge. Therefore the common problem of making decisions is that decisions are not made reliable enough because parameters in risk assessment and supply chain management are underestimated or not robust enough. In this paper we propose a framework that will try to predict future situations collectively and increase the reliability of decision making. Project management is the art of making right decision. Project managers are faced by huge array of choices. Decision analysis is used in strategic planning, operational management, and other areas of business. Decision analysis helps companies to determine optimal exploration and production strategies with uncertainties in cost, prices, and exploration prospects. This paper describes project management steps and the way they can be supported by Intelligent Decision Support system (IDSS). The main parameters assessed are total cost of the projects, time of the project total fulfilment, number of subcontractors, location factors, and etc. IDSS will enable to collect data, propose possible alternative decisions, and provide risk assessment.

5

IDSS used as a framework for collaborative projects in conglomerate enterprises

Shevtshenko E., Karaulova T., Kramarenko S., Wang Y.

Journal of Achievements in Materials and Manufacturing Engineering

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2007

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Vol. 22, nr 1

89-92

EN

Purpose: of this paper is to summarize the application study of the general framework of intelligent decision support system (IDSS) to collaborative projects in conglomerate enterprises. Today's market competition requires project managers to make correct decisions fast. In some situations, even with the knowledge of how to find right information and which decision making methods to apply, people do not have enough time to make right decisions at the right time. In this paper, the frame work of an IDSS system to support real-time collaboration and enable seamless data exchange is presented. The IDSS system is able to support the information flow between internal and external sources. Data are shared, prepared, and streamlined to appropriate analytical tools. A case study of manufacturing projects in a specific European shipbuilding conglomerate is used to illustrate the process and usefullness of IDSS in combination with Enterprise Resource Planning (ERP) systems. Design/methodology/approach: A model of internal and external information flows is proposed for enterprise information management. The important roles of facilitation and organization that the IDSS plays are demonstrated. In the case study examples of manufacturing projects analysis are given with the known methods, including Analytical Hierarchy Process and Bayes Rule. Findings: It was found that IDSS is an essential component to enhance decision makings with complex information flows in large conglomerates. Main conclusions is to show what we will achieve through IDSS systems, to show how perform analysis in logical way. Research limitations/implications: The functionality of the developed framework is limited by the willingness of management style and culture changes in companies, as well as the level of interoperability between commercial software components. Practical implications: Project engineers and managers need to adapt to the new IT-based working environment. Intensive use of software tools may become the major challenge for those who cannot absorb information based on the new format of information presentation. Originality/value: The proposed new information management model and the framework of IDSS system enable ease of data sharing and processing by internal and external stakeholders in decision makings. The collaborative decision making consists of different parts: the management of information flow, the preparation of data for decision making, and actual decision making supported by several methods.