Avraham Shtub

Constructing and evaluating balanced portfolios of R&D projects with interactions: A DEA based methodology

We propose and demonstrate a methodology for the construction and analysis of efficient, effective and balanced portfolios of R&D projects with interactions. The methodology is based on an extended data envelopment analysis (DEA) model that quantifies some the qualitative concepts embedded in the balanced scorecard (BSC) approach. The methodology includes a resource allocation scheme, an evaluation of individual projects, screening of projects based on their relative values and on portfolio requirements, and finally a construction and evaluation of portfolios. The DEA–BSC model is employed in two versions, first to evaluate individual R&D projects, and then to evaluate alternative R&D portfolios. To generate portfolio alternatives, we apply a branch-and-bound algorithm, and use an accumulation function that accounts for possible interactions among projects. The entire methodology is illustrated via an example in the context of a governmental agency charged with selecting technological projects. � 2005 Elsevier B.V. All rights reserved.

Business Process Improvement

For a process-centric organization, the management and improvement of its business processes is an essential factor in organizational advancement. From the same perspective, the implementation and change of these processes has all the facets of Change Management - including managerial disputes about the nature of advancement; a socio-cultural challenge resulting from the severe organizational effects on the involved people, which may lead them to react against those changes; and a technical challenge, which is due to the difficulty in developing a business process redesign which aims towards an improvement of the current design (Reijers and Mansar 2005; Carr and Johansson 1995). To keep pace with the ever-changing environment, organizations need to be aware of their ability to adapt. Business Process Management is one approach to enhance internal efficiency and to change the way the organization functions (Forster 2006b). In effect, Business Process Management is an essential part of enterprise management. For an in-depth review of Business Process Management the reader is referred to the many books on this topic (see, for example, Jeston and Nelis 2006). Within the scope of this book, we focus on one aspect: the modification and improvement of business processes resulting from problems such as dissatisfaction with current processes, feedback from process performers and customers, changes in the modus operandi of the organization, enhancement of IT and knowledge resources, and adaptation of the enterprise to developments in the external environment.

Sequencing mixed-model assembly lines to level parts usage and minimize line length

Abstract The problem of sequencing units on a mixed-model assembly line can be viewed with several objectives in mind. Past research has focused mainly on two separate performance measures: (1) minimizing the length of the line (which is equivalent to minimizing the risk of stopping the conveyor when system variability is present and the station lengths are fixed); or (2) maintaining a rate of assembly equal to the demand rate for each model type in the production schedule. The latter is the more appropriate in a just-in-time environment. We present a bicriteria formulation of the problem that can be used to examine the tradeoffs between line length and parts usage. The resultant model takes the form of a mixed integer nonlinear program and is solved with a combination of heuristics and branch and bound. Results are reported for a wide range of problem sizes, as defined by the number of stations on the line, the number of different model types, and the total number of units to be assembled. In almost all ...

The Impact of Breaks on Forgetting When Performing A Repetitive Task

Commonly used learning curve models assume that a repetitive task is performed continuously, disregarding the existence of possible break periods between consecutive repetitions. Since these breaks generate forgetting, actual performance will be inferior to the performance forecasted by typical learning curve models. This paper describes and analyzes a laboratory experiment designed to investigate the nature of forgetting in a working environment. The results of the experiment indicate that the degree of forgetting is a function of the break length and the level of experience gained prior to the break. The study investigated the impact of breaks within a range of one to eighty two days. The performance deterioration due to the breaks was just a few percentage points for a single day break and up to 70 percentage points for the longest breaks. A power curve was identified as a proper forgetting model to depict the relationship between break length, performance time before the break and the degree of forget...

Estimating the cost of steel pipe bending, a comparison between neural networks and regression analysis

Abstract Design to cost and cost based competition focus on the relationship between design decisions and the resulting cost of manufacturing, supporting and operating products. The efforts to optimize the value (measured in terms of cost/benefit ratio) of products early on in the design process motivated the development of a variety of cost estimation tools. Automatic tools linked directly to the computer aided design (CAD) system and producing cost estimates based on the CAD data are the ideal. However, most of the cost estimating systems available today cannot read the CAD data files directly – the input of these tools include two types of information: 1. Technical, objective information (independent of the person using the system, e.g. the geometry of parts, materials used and dimensions) and 2. Subjective information (e.g. an estimate of the quantities that will be manufactured each period during the products life cycle). Modern cost estimating systems are based on a combination of a model base and a database. The users who collect the data on actual cost of products usually update the database. The model base has to be updated whenever the technology changes and new processes and materials are made available or when new estimation models are developed. The users cannot frequently update the model base of a cost estimating system. They are dependent on the software suppliers that release new versions of the software with the required updates. In this paper, we describe a cost estimating system that can be linked to the CAD data. The parameters used as input to the cost estimation model are objective and easily available. The proposed system is based on a neural network that learns how to modify cost estimates when a new technology is developed. A comparative study reveals that the proposed system outperforms traditional linear regression analysis models used for cost estimation.

Simulation-based models of emergency departments:: Operational, tactical, and strategic staffing

The Emergency Department (ED) of a modern hospital is a highly complex system that gives rise to numerous managerial challenges. It spans the full spectrum of operational, clinical, and financial perspectives, over varying horizons: operational—a few hours or days ahead; tactical—weeks or a few months ahead; and strategic, which involves planning on monthly and yearly scales. Simulation offers a natural framework within which to address these challenges, as realistic ED models are typically intractable analytically. We apply a general and flexible ED simulator to address several significant problems that arose in a large Israeli hospital. The article focuses mainly, but not exclusively, on workforce staffing problems over these time horizons. First, we demonstrate that our simulation model can support real-time control, which enables short-term prediction and operational planning (physician and nurse staffing) for several hours or days ahead. To this end, we present a novel simulation-based technique that implements the concept of offered-load and discover that it performs better than a common alternative. Then we evaluate ED staff scheduling that adjusts for midterm changes (tactical horizon, several weeks or months ahead). Finally, we analyze the design and staffing problems that arose from physical relocation of the ED (strategic yearly horizon). Application of the simulation-based approach led to the implementation of our design and staffing recommendations.

Scheduling projects to maximize net present value -- the case of time-dependent, contingent cash flows

Abstract The problem of scheduling activities in a project to maximize its Net Present Value (NPV) has been solved for the case where net cash flow magnitudes are independent of the time of realization. This paper models a more realistic version of this problem — because of incentive payments and penalties for early and late event occurrences, respectively, and because of changing costs of resources over time, net cash flow magnitudes are dependent on the time of realization. We formulate an optimization program for this more general problem and present a simulated annealing solution approach. We test different implementation strategies for this algorithm and suggest a method for choosing neighborhood moves. We compare the NPVs of the solutions obtained from our formulation with the NPVs of early start schedules and with late start schedules for 168 different problems. These computational results show that the simulated annealing approach consistently produces substantially better solutions than the early start or late start schedules. Even poor simulated annealing neighborhood moves give improved solutions for most problems studied.

A methodology for the selection of assembly systems

The design of an assembly system for a particular product is a complex engineering effort involving many interrelated decisions. The wide range of alternative system configurations makes a detailed design of each alternative too expensive and time-consuming. In this work a methodology is developed which helps the decision maker by ranking possible alternatives according to ‘subjective’ cost/ benefit criteria.

A framework for teaching and training in the Enterprise Resource Planning (ERP) era

The development of new generations of information systems, known as Enterprise Resource Planning (ERP) systems, generated a gap between the knowledge that managers need to use these systems efficiently and effectively, and the curriculum of most traditional academic programs. This gap is due to the difference between the integrated approach of ERP systems, which supports complete processes, and the approach of most Industrial Engineering and management courses, which focus on specific functions such as Marketing, Operations, Finance or Purchasing. This paper presents a new framework for teaching and training in the ERP era. A methodology for teaching processes is presented along with a special training tool that combines an interactive, dynamic case study and an educational version of an ERP-like Management Information System. The tool and the methodology form a framework for teaching individuals and teams. The framework is designed to facilitate individual learning and to provide an environment that enhances and supports teamwork in managing the order fulfilment process. The experience accumulated with the methodology and its supporting training tool over the last three years reveal that it is very effective in teaching the concepts of ERP, workflow and team decision making. The proposed framework was used in Universities in Business schools and in Industrial Engineering programs. It was also used in workshops in industry, training managers interested in ERP and its implementation.

Managing Stochastic, Finite Capacity, Multi-Project Systems through the Cross-Entropy Methodology

This paper addresses the problem of loading a finite capacity, stochastic (random) and dynamicmulti-project system. The system is controlled by keeping a constant number of projects concurrently in the system. A new approach, based on the Cross-Entropy (CE) method, is proposed to determine optimal loading of the system. Through numerical experiments, we demonstrate the CE method performance and show new insights into its behavior in a noisy system. Particularly, we suggest a trade-off between the convergence time, the number of iterations and the noise level.