Monday, June 01, 2009

Using system dynamics, neural nets, and eigenvalues to analyse supply chain behaviour - A case study

Full Citation
Rabelo, L., Helal, M., Lertpattarapong, C., Moraga, R., Sarmiento, A. 2008. Using system dynamics, neural nets, and eigenvalues to analyse supply chain behaviour - A case study. International Journal of Production Research, (46) 1: 51 – 71.

Abstract
This paper presents a new analysis approach to detect behavioural changes in manufacturing supply chains due to endogenous and/or exogenous influences and forecast the impact of these changes in the short and long term horizons. First a dynamic model of the supply chain is developed using system dynamics simulation. Afterward, Neural Networks, which can be encapsulated in software agents, are utilized to detect the changes at a very early stage so that an enterprise would have enough time to respond and counteract any unwanted situations. Then, principles of stability and controllability are used to apply and make modifications to the information and materials flows to adapt to the changes and avoid the expected behaviour. A case study of an actual electronics manufacturing company demonstrates the methodology developed.
Keywords: Supply chain modelling, System dynamics, Neural Nets, Eigenvalue analysis

Creative solutions for analyzing faculty and administrator salaries

Full Citation
Helal, M., Archer, S., Armacost, A. 2008. Creative solutions for analyzing faculty and administrator salaries. Florida Association for Institutional Research; FAIR Conference, Feb 6-8, Indialantic, FL

Abstract
The recruitment and retention of talented faculty is critical to instructional quality and the growth and enhancement of research at higher education institutions. At the same time, these institutions are challenged with the need to recruit and retain administrators to ensure continuous operations and to facilitate progress toward the mission of the institution. There are various approaches to examining salary equity, each addressing different research questions. The purpose of this poster is to display a suite of decision support tools that were developed to answer specific questions regarding annual wage increases and to explore if groups of administrators and faculty members were not correctly compensated. Technologies were employed to provide a flexible tool for evaluating salary information at various levels of detail to provide a comprehensive analysis. There are many data sources available to researchers and methods by which to conduct salary studies. The initial challenge in approaching this study was gaining an understanding of the various data sources and the potential information these data sources might provide, as well as their limitations. There were several analytical paths attempted, but after limitations of data sources were reached, creative solutions were developed to provide subject matter experts a suite of data tools that provide data visualization and various levels of detailed comparisons using data available from the state. This poster will describe the various data sets initially employed in initial studies and their potential use. Finally, solutions developed that provided subject matter experts with decision support tools will be showcased. The challenges in data collection, visualization, and maintenance will be explained. The salary equity analytical tools were developed using MS Visio 2003 and Excel 2003. Base SAS 9.3.1 SP 3 code is written to compile data in a form that was usable in both Visio and Excel PivotTables. This presentation is intended for institutional researchers interested in learning about various salary equity data sources and their potential uses as well as decision support tool development.

Introduction to VBA in MS Excel

Full Citation
Helal, M., Archer, S. 2008. Introduction to VBA in MS Excel. Florida Association for Institutional Research; FAIR Conference, Feb 6-8, Indialantic, FL

Abstract
Almost every institutional researcher uses MS Excel. But using Excel can be time consuming when working with thousands of data records, or when having to repeat the same tasks time after time. Visual Basic for Applications (VBA) is a version of the Visual Basic programming language that is included in MS Excel as a standard add-in. Excel VBA is designed to allow Excel users to control cell ranges, sheets, workbooks, charts, formulas, and most other Excel objects and tools. VBA code subroutines in Excel are termed macros. Macros may be saved in the Excel workbook or globally and are reusable and editable as necessary. Graphical user interfaces can be built to interact with workbook contents, thus users do not have to work directly with the data. Several macros can be written for each workbook to perform customized Excel functions and tasks, which can lead to more efficiency and accuracy. However, working with programming languages intimidates many people. This presentation is an introduction to writing Excel VBA macros for common data manipulation tasks. A simple Excel VBA application will be used to demonstrate each of the following:
1. Recording and editing VBA macros
2. Inserting a graphical user interface and linking it to the VBA code
3. Editing and moving data between sheets and workbooks
4. Formatting data cells and executing some formulas and operations
5. Creating and controlling pivot tables and filters

Each of these tasks will be explained and presented such that no knowledge of computer programming is necessary. After attending the presentation, an Excel user with no knowledge of computer programming should be ready to start exploring the potentials of using VBA in their everyday Excel tasks.

Value chain analysis using hybrid simulation and AHP

Full Citation
Rabelo, L., Eskandari, H., Shaalan, T., Helal, M. 2007. Value chain analysis using hybrid simulation and AHP. International Journal of Production Economics, (105): 536-547.

Abstract
This paper presents a novel approach that integrates the analytic hierarchy process (AHP) technique, system dynamics (SD), and discrete-event simulation (DES) to model the service and manufacturing activities of the global supply chain of a multinational construction equipment corporation. Hybrid SD–DES simulation models offer a practical approach to better model real-life systems and increase confidence in their outcomes. The DES models are developed using the supply chain operations reference (SCOR) model to guide the modeling process. Managers evaluate the competing decision alternatives based on the obtained simulation results of the hybrid models and other qualitative factors using group AHP analysis. This integration enables managers to utilize their own experiences, preferences and qualitative assessments which increases the level of their confidence in the decisions resulting in the maximization of shareholder value.
Keywords: Discrete-event simulation; System dynamics; AHP; SCOR; Supply chain

Technology solutions to support program of study planning and class scheduling

Full Citation
Archer, S., Helal, M., Sehrish, S., Armacost, R. 2007. Technology solutions to support program of study planning and class scheduling. 34th Annual Southern Association of Intuitional Research Conference; SAIR, Oct 7-9, Little Rock, AR

Abstract
Academic career plans may be jeopardized when deviation from the plan occurs such as failing a course with matters made worse when that class is a prerequisite for others. Sometimes, even the best plans are infeasible when courses are offered at conflicting times during the same semester. This presentation demonstrates technology solutions that have been developed to provide advisors with individualized programs of study that account for students’ unique academic situations as well as student class schedules. The various assumptions, data requirements, and challenges are discussed along with implementation using Excel and SAS/OR.

A methodology for integrating and synchronizing the system dynamics and discrete event simulation paradigms

Full Citation
Helal, M., Rabelo, L., Sepulveda, J., Jones, A. 2007. A methodology for integrating and synchronizing the system dynamics and discrete event simulation paradigms. Proceedings of the 2007 International Conference of the System Dynamics Society, July 29 – Aug 2, Massachusetts, MA.

Abstract
With the adoption of integration and system perspectives in managing the manufacturing systems and the pressure imposed by the increased competition and rapidly changing business environment, the need has arisen for new approaches for simulating the manufacturing enterprise. We have proposed SDDES; a hybrid System Dynamics Discrete Event Simulation approach to simulating the integrated manufacturing enterprise. SDDES offers comprehensive simulation models that encompass all management levels and recognize the differences between them in terms of scope and frequency of decision making as well as the levels of details preferred and used at each level. SDDES maintains the integrity of the two simulation paradigms and can use existing/legacy simulation models without requiring learning new simulation skills. In this paper we describe the modular structure of SDDES, our method to synchronize and coordinate SD and DES, and the functional model of the SDDES controller, which manages the integration of the two simulation methodologies.

Keywords: Hybrid continuous-discrete simulation – Manufacturing enterprise - System dynamics – Discrete event simulation

A Hybrid System Dynamics Discrete Event Simulation Approach to Simulating the Manufacturing Enterprise

Full Citation
Helal, M., Jones, A., Rabelo, L. 2007. Hybrid system dynamics-discrete event simulation approach to simulating the manufacturing enterprise. INFORMS International Conference: Puerto Rico 2007, July 8-11

Abstract
We describe a methodology to integrate system dynamics (SD) simulation and discrete event simulation (DES) for simulating the manufacturing enterprise. Previously we have shown that SD and DES can complement each other for that purpose. The methodology calls for a modular structure for the simulation models that we describe here. We also propose a synchronization mechanism and describe the design of the communication controller unit that will manage the integration of the two simulation paradigms.

Tabu search algorithm for the unrelated parallel machines scheduling problem with setup times

Full Citation
Helal, M., Rabadi, G., Al-Salem, A. 2006. Tabu search algorithm for the unrelated parallel machines scheduling problem with setup times. International Journal of Operations Research, (3) 3: 1-11

Abstract
Abstract: In this paper we propose a tabu search implementation to solve the unrelated parallel machines scheduling problem with sequence- and machine- dependent setup times to minimize the schedule’s makespan. The problem is NP-hard and finding an optimal solution efficiently is unlikely. Therefore, heuristic techniques are more appropriate to find near-optimal solutions. The proposed tabu search algorithm uses two phases of perturbation schemes: the intra-machine perturbation, which optimizes the sequence of jobs on the machines, and the inter-machine perturbation, which balances the assignment of the jobs to the machines. We compare the proposed algorithm to an existing one that addressed the same problem. The computational results show that the proposed tabu search procedure generally outperforms the existing heuristic for small- and large-sized problems.
Keywords: Tabu Search, Scheduling, Unrelated Parallel Machines, Setup Times

Detecting and Analysing Patterns in Supply Chain Behavior

Full Citation
Rabelo, L., Helal, M., Dawson, J., Moraga, R. 2006. Detecting and analyzing patterns in supply chain behavior. International journal of simulation and process modeling, (2)3/4: 198-209

Abstract
Using outputs of a supply chain system dynamics model, neural networks’ patternrecognition capabilities and eigen value analysis are utilised to detect and analyse behavioural changes in the supply chain and predict their impact in the short- and long-term horizons on performances. Neural networks are used to detect changes in the supply chain behaviour at a very early stage of their occurrence so that an enterprise would have enough time to respond and
counteract any unwanted situations. Then, the principles of stability and controllability are used to apply and make modifications to the information and material flows to avoid undesirable behaviours.
Keywords: supply chain modelling; supply chain management; SCM; system dynamics; SD;
neural networks; NNs; eigen value analysis

Using hybrid SD-DES for the simulation of the manufacturing enterprise

Full Citation
Helal, M., Rabelo, L., Jones, A. 2006. Using hybrid SD-DES for the simulation of the manufacturing enterprise. The French-US Workshop on ICT and Standards for Supply Chains and PLM. Nov 6-7; NIST, Gaithersburg, MD

Extended Abstract
For decades, discrete event simulation (DES) has been the modeler’s choice for simulating the manufacturing systems. It has effectively allowed analysts model systems to the deepest level of details. Yet with the adoption of integration and system approaches in managing the manufacturing system and the pressure imposed by the increased competition and rapidly changing business environment, the need has arisen for different simulation modeling tools. Managers need to overcome the traditional organizational barriers and run their facilities in a more flexible, coordinated and dynamic manner.

However, more integration in manufacturing systems increases the levels of complexity. The need is for simple comprehensive simulation tools that help achieving coordination while being able to handle the dynamics of the complex system processes. Such tools must be holistic, easy to comprehend, and able to offer decision makers at the various management levels the appropriate levels of details that suit each of them, and reflect the impact of decisions in an enterprise-wide fashion.

We propose to combine the system dynamics (SD) methodology (Forrester, 1965) and DES in a hybrid approach to simulate the manufacturing enterprise. This combines the effectiveness of DES with the simplicity and overall system thinking approach of SD. Manufacturing enterprises consist of manufacturing and non-manufacturing functions. Including aggregate and operational levels of management in the same simulation model has become essential to correctly assess the enterprise performance. Using the most advanced equipment and producing the same product quality as competitors do not offer a competitive advantage (Wu, 1992) unless marketing, customer relations, financial aspects and other professional supporting functions are coordinated. Implementing a total quality management (TQM) program can dramatically improve the operational level performance while leading to significant decline in financial performance (Sterman et al., 1997) unless coordination with an overall simulation model of the organization is utilized. Further, approximating continuous system parameters with DES simulation models would lead to overestimating or underestimating the performance of the system (Lee et al., 2002). Many published reports have clearly indicated the need to combine the aggregate and operational levels of management in simulating the system.

There are always detailed data available for the manufacturing functions. But for the aggregate management level non-manufacturing functions, data is not usually available and in most cases only rough estimates exist. DES has been successful in conducting detailed manufacturing systems analyses such that the status of individual entities and resources can be monitored. Its outputs are given as estimates of and correlations among variables and performance measures using statistics, which are not easily understandable, especially for the case of an integrated large sized manufacturing system. Further, DES allows the evaluation of the performance for specific values of decision variables or control policies, but analyzing the stability of the system in any region or neighborhood of those values or policies is not supported (Rabelo et al., 2005). Add to that DES models rapidly become very complex with the size of the system being modeled.

SD on the other hand is a system thinking approach that targets top management levels. It addresses the impact of the system structure and inherent feedback interactions among its component, on performance. Its data requirements are minimal and it offers aggregate level managers an integrative approach to analyze the nonlinear, overlapping cause-and-effect relationships in their systems. Nevertheless, using SD at the operational levels has failed to offer the desirable outcomes.

In our hybrid SD-DES approach the enterprise model consists of a comprehensive SD model for the total enterprise system connected with a number of DES models for the parts in the system that require detailed analyses. This offers managers the needed comprehensive, simple, yet scalable approach to design and test management policies in an integrated system perspective.

However, due to the differences between the two modeling paradigms, coordinating the interactions among the SD and DES models and synchronizing the simulation time pose a challenge. Traditionally, hybrid discrete-continuous simulations have been based on control situation requirements in which a discrete system controls a continuous variable based on a preset threshold value or on/off-like discrete events (Ziegler et al., 2002; Maler et al., 1992).

We argue that such control approaches are not fully appropriate for the business systems as they normally result in discontinuous behaviors of the continuous parameters and unavoidable dominance of the discrete components. We describe the conceptual design of the SD-DES controller whose functions are the coordination and synchronization of interconnected SD and DES simulation models without having one approach dominating the other. We here discuss the considerations and challenges in achieving the synchronization of the interacting models. We also, investigate the perspectives for implementing the SD-DES controller as a generic software application.

Interactions of the Three Management Levels in the Manufacturing Enterprise System Using Hybrid Simulation

Full citation
Helal, M., Rabelo, L. 2006. Interactions of the three management levels in the manufacturing enterprise system using hybrid simulation. IERC 06; The IIE Annual Research Conference, May 20-24 Orlando, FL

Abstract
We build on our previous work of developing a hybrid discrete-continuous simulation model of the manufacturing enterprise system. This model consists of an overall system dynamics model of the enterprise and connected to it are a number of discrete event simulations for selected operational and tactical functions. System dynamics modeling best fits the macroscopic nature of activities at the higher management levels while the discrete models best fit the microscopic nature of the operational and some tactical levels. This offers a simple, scaleable, non-expensive dynamic policy design tool that fits the different scopes and planning frequencies of management levels. In this paper we report the progress being made in designing the process of communication between the continuous system dynamics model and the discrete models. We discuss the characteristics and considerations that must be investigated while devising the controller unit that facilitates and synchronizes the integration of the simulation models.

Keywords: Hybrid Simulation, Discrete Event Simulation, System Dynamics, Manufacturing Enterprise

Spreadsheet model approaches for university class schedules

Full Citation
Helal, M., Armacost, R., Adams, D. 2005. Spreadsheet model approaches for university class schedules. Southern Association of Intuitional Research Conference; SAIR, Oct 22-25, Charleston, SC.

Abstract
Responding to pressures to have students graduate in four years, a large university has instituted a Graduate On Track program that guarantees a seat in all classes needed to graduate in the four-year period. The technical challenge is to construct a feasible class schedule that identifies which sections of which courses need seats to be reserved. This presentation describes an Excel spreadsheet-based methodology used to generate such schedules for each major. The methodology involves identifying feasible solutions to an embedded optimization problem using the Solver add-in in Excel. The presentation also identifies the technical and operational implementation challenges.

Supporting Simulation-Based Decision Making With the Use of AHP Analysis

Full Citation
Rabelo, L. Eskandari, H., Shalan, T., Helal, M. 2005. Supporting simulation-based decision making with the use of AHP analysis. Winter Simulation Conference, WSC’05, December 4-7, Orlando, FL.

Abstract
Traditionally decisions made based on simulation models have been the outcomes of complicated statistical analyses and having confidence in them is a subjective matter. Hybrid simulation offers an improved approach to better model real life systems and increase confidence in their outcomes. In particular hybrid discrete-continuous simulation has the potentials to reduce the impact of statistics in building models in addition to other significant benefits. In this paper we use hybrid models of discrete-event simulation and system dynamics to analyze global supply chain decisions. And to increase the decision makers’ confidence as well as to make use of their experiences we apply the Analytic Hierarchical Process (AHP) analysis to the simulation results in order to reach better decisions. We describe the benefits of the use of the hybrid simulation and the added advantages of using AHP in order to maximize shareholder value.

Enterprise simulation: a hybrid system approach

Full Citation
Rabelo, L., Helal, M., Jones, A., Min, H. 2005. Enterprise simulation: A hybrid system approach. International Journal of Computer Integrated Manufacturing, (18) 6: 498-508

Abstract
Manufacturing enterprise decisions can be classified into four groups: business decisions, design decisions, engineering decisions, and production decisions. Numerous physical and software simulation techniques have been used to evaluate specific decisions by predicting their impact on either system performance or product performance. In this paper, we focus on the impact of production decisions, evaluated using discrete-event-simulation models, on enterprise-level performance measures. We argue that these discrete-event models alone are not enough to capture this impact. To address this problem, we propose integrating discrete-event simulation models with system dynamics models in a hybrid approach to the simulation of the entire enterprise system. This hybrid approach is conceptually consistent with current business trend toward integrated systems. We show the potentials for using this approach through an example of a semiconductor enterprise.

Pattern Recognition in Supply Chain Management

Full Citation
Rabelo, L., Helal, M., Sepulveda, J. 2005. Pattern recognition in supply chain management. in Liu, Y., Chen, G., Ying, M. (Eds.): Fuzzy Logic, Soft computing, and Computational Intelligence, pp 1961-1735, Springer, Tsinghua University Press, Beijing, China

Abstract
This paper introduces a methodology to recognize patterns of behavior and optimize the supply chain. System Dynamics is used to model the supply chain. Neural Networks are utilized to detect the changes at a very early stage and predict their impact. Then, decomposition, linearization, and eigenvalue analysis are used to apply and make modifications to the information and materials flows to avoid any undesirable expected behavior.
Keywords: Supply chain behavior, system dynamics, eigenvalue analysis, neural networks, pattern recognition

Analysis of Supply Chains Using System Dynamics, Neural Nets, and Eigenvalues

Full Citation
Rabelo, L., Helal, M., Lertpattarapong, C. 2004. An analysis of the supply chains using system dynamics, neural nets and eigenvalues. The Winter Simulation Conference, WSC’04, Dec 5-8, Washington DC

Abstract
Supply chain management is a critically significant strategy that enterprises depend on in meeting the challenges of today’s highly competitive and dynamic business environments. An important aspect of supply chain management is how enterprises can detect the supply chain behavioral changes due to endogenous and/or exogenous influences and to predict such changes and their impacts in the short and long term horizons. A methodology for addressing this problem that combines system dynamics and neural networks analysis is proposed in this paper. We use neural networks’ pattern recognition abilities to capture a system dynamics model and analyze simulation results to predict changes before they take place. We also describe how eigenvalue analysis can be used to enhance the understanding of the problematic behaviors. A case study in the electronics manufacturing industry is used to illustrate the methodology.
Keywords: Supply chain, system dynamics, neural nets, Eigenvalues

An Enterprise Simulation Approach to the Development of a Dynamic Balanced Scorecard

Full Citation
Helal, M., Rabelo, L. 2004. An enterprise simulation approach to the development of dynamic balanced scorecards. ASEM’04; Proceeding of 2004 American Society of Engineering Management Conference, October 20-23, Alexandria, Virginia

Abstract
The balanced scorecard seeks to provide managers with a comprehensive set of measures of performance of the organization. However, almost only big organizations could successfully implement scorecards and numerous failures have been reported. We argue that the causes of failure are fundamentally the inevitable subjectivity inherent in the methodology and the lack of a reliable tool to guide the implementation process. We recently proposed a hybrid approach using discrete event simulation and system dynamics to total enterprise simulation modeling. In this paper we explore the merits of using the enterprise simulation model to support management in developing the balanced scorecard.
Keywords: dynamic balanced scorecard, system dynamics, enterprise simulation

Detecting Changes and Avoiding Unwanted Behavior in Supply Chains

Full Citation
Rabelo, L., Helal, M., Lertpattarapong, C. 2004. Detecting changes and avoiding unwanted behavior in supply chains. PICMET’04 Symposium ; Portland International Center for Management of Engineering and Technology, July 31 - August. 4, 2004, Seoul, Korea

Abstract
The new forces of globalization, advances in web technologies, new methodologies/tools to integrate engineering and business functions, the developments in e-commerce and their complex interrelationships are shaping the competitive landscape of business. Organizations are looking for strategies to meet these challenges and take advantage of new opportunities. One of such strategies is supply chain management. This paper introduces a methodology to detect changes in supply chain behaviors due to endogenous and/or exogenous influences, and predict the impact of these changes in the short and long term horizons. System Dynamics is used to model the dynamic supply chain behavior. Neural Networks, which can be encapsulated in software agents, are utilized to detect the changes at a very early stage so that enterprises have enough time to respond and counter-effect any unwanted situations. Then, principles of stability and controllability are used to apply and make modifications to the information and materials flows to adapt to the changes and avoid the undesirable behavior. A case study of an actual electronics manufacturing company is used to demonstrate the methodology.
Keywords: Supply chain, syytem dynamics, eigenvalue analysis

Investigating Group-Scheduling Heuristics In The Context Of The Two-Phase Nature Of The Model In A Flow Cell

Full Citation
Helal, M., Rabelo, L. 2004. Investigating group-scheduling heuristics in the context of the two-phase nature of the model in a flow cell. IERC 04, The IIE Annual Conf., May 15-17 Houston, TX

Abstract
In the group scheduling model jobs are classified into part families according to the setting and processing requirements. The scheduling task becomes a two-phase job: to schedule part families and to schedule jobs within each part family. Several important advantages can be realized with this approach. One advantage is greatly simplifying the scheduling problem. Yet it is a NP-hard problem and heuristic algorithms are used to solve it. We have classified the published heuristics into three categories based on the complexity of the method. Further, a number of modifications have been tested to investigate the relative performance of the heuristics in a multi-family, flow line manufacturing cell. We comment on the results in the context of the two-phase nature of the group-scheduling model.
Keywords: Group scheduling, Heuristics, Tabu search, Simulated annealing, Makespan

A Study of the Impact of Production Scheduling Using Enterprise Simulation

Full Citation
Helal, M., Rabelo, L., Jones, A. 2004. A study of the impact of production scheduling using enterprise simulation. IERC 04, The IIE Annual Conference;, May 15-17 Houston, TX

Extended Abstract
The strong tendency toward more integration in businesses and the system thinking approaches are shaping the way manufacturing enterprises are being managed, especially in an environment of market globalization, ever varying customer requirements and increasing competition. As a result, the development of manufacturing simulation systems is directed toward integrated enterprise modeling in two directions of integration: horizontally by integration of manufacturing processes with the entire enterprise logistics chain, and vertically by integration of the decision making processes at the strategic, tactical and operational management levels [1]. To achieve a competitive advantage an enterprise must cope with these trends and changes in the working environment.

In this work, we introduce a hybrid simulation approach that combines discrete-event models with system dynamics models to simulate the entire manufacturing enterprise system. This approach basically covers the strategic, tactical, and operational levels of decision-making in a single simulation of multiple models at different levels and resolutions. System dynamics (SD) is utilized to model the higher levels of decision-making in the enterprise, while discrete-event simulation (DES) models are utilized for the factory and shop floor levels. Studying the interaction between strategic planning and the production activities is the core of this work.

Discrete event simulation has been the most usable simulation tool in manufacturing applications. It has the ability to describe the most complex systems at any level of details while allowing tracking the status of individual entities and resources and estimating numerous performance measures associated with these entities under various operating conditions. This makes it the most appropriate approach to simulate the detailed manufacturing activities.

At the higher levels of decisions making, which are mainly non-manufacturing tasks, the detailed approach of DES is not as appropriate [2,3,4]. For one reason the decision makers at these levels do not prefer detailed analyses. In addition unlike manufacturing tasks data, the non-manufacturing tasks data are only available as rough estimates [5]. For that we consider SD simulation, which is a system thinking approach that focuses on the structure of the system and its dynamic behavior due to taken management policies, for simulating these levels. SD is not a data-driven approach and its data requirements are minimal. The central concept in SD is that all the components of a system interact through causal relationships that come about through feedback loops. Thus a model is a dynamic picture of the perceived cause-and-effect relationship among system components. It can easily incorporate continuous and qualitative systems parameters as well. These features make SD well appropriate for simulating strategic and tactical decision making processes.

It is understandable that the driving force for a company’ strategic planning is its need and desire to manufacture competitive products. Operational scheduling on the other hand refers to the short-term decision problems in executing the company’s business strategies and achieving the planned goals. Traditionally planning and scheduling used to be very distinct phases. Such distinction does not match the requirements of the current operating environments. However a practical holistic approach to coordinate and integrate them is not yet available. The proposed hybrid simulation approach offers this holistic approach.

We consider a semiconductor enterprise, which typically works in a very dynamic and capital intensive industry. Top management decides based on market analysis to introduce a new generation of chips or enter a new electronics market. Scheduling receives a set of orders and designed goals with predefined release dates for the raw materials and due dates for finished products. Given the time consuming processes involved in semiconductor manufacturing operations, scheduling is a complicated task that would involve the design of new processes that should consider the cost constraints of the management. The related strategic resource allocation decisions made at the enterprise levels in order to be implemented at the production level have strong impact on the effectiveness of the scheduling and other production functions. Reciprocally the effectiveness in executing top management plans to supply the required demand and in using the allocated resources at the operational and tactical levels has direct impact on the ability of the enterprise to satisfy its market commitments and on its financial performance as well.

Further when more than production plants exist within the enterprise (which is the case for a wide range of current manufacturing enterprises) the situation becomes more complicated especially when the different plants work at different levels of performance and have different impacts and contributions to the enterprise’s profitability.

Planning, marketing and customer relations management functions at the strategic levels must be in close coordination with the shop floor level functions. Real time data reflecting the shop floor status must be available during the review of the business strategies and during deciding on introducing new products or entering new markets as well as during making the resources allocation decisions. These decisions must be made fast enough to seize available market opportunities which are always the target of many competitors. In addition to being fast, they should be reliable and based on feedback from all participants, so that later modifications and corrections, which are usually more costly, are eliminated or minimized.

This proposed hybrid simulation environment provides the practical framework to achieve the needed integration. It is utilized to study the impact of the top management decisions (such as resource allocation and new product decisions) on developing production schedules and capacity management at the operational levels. Equivalently it allows for studying and monitoring the execution of strategic plans at all levels. The backbone of the methodology is the use of the feedback information going back and forth between the SD model (higher management levels) and the DES models (lower management levels). Management policies can then be tested in an overall approach, before being executed. This also leads to better communications among all levels of management and can increase the role of the tactical and operational levels in the design of the strategic policies.

Keywords: Scheduling, Enterprise simulation, System dynamics, Hybrid simulation

A Hybrid Approach to Manufacturing Enterprise Simulation

Full Citation
Rabelo, L, Helal, M., Son, Y., Jones, A., Min, J., Deshmukh, A. 2003. A hybrid approach to manufacturing enterprise simulation. Winter Simulation Conference, WSC’03, December 7-10, New Orleans, LA

Abstract
Manufacturing enterprise decisions can be classified into four groups: business decisions, design decisions, engineering decisions, and production decisions. Numerous physical and software simulation techniques have been used to evaluate specific decisions by predicting their impact on the system as measured by one or more performance measures. In this paper, we focus on production decisions, where discrete-event simulation models perform that evaluation. We argue that such an evaluation is limited in time and scope, and does not capture the potential impact of these decisions on the whole enterprise. We propose integrating these discrete-event models with system dynamic models and we show the potential benefits of such an integration using an example of semiconductor enterprise.
Keywords: Manufacturing Enterpise, hybrid simulation, discrete vent simulation, System dynamics

A Tabu Search Approach for the Non-identical Parallel-Machines Scheduling Problem With Sequence-Dependent Setup Times

Full Citation:
Helal, M., Hosni, Y. 2003. A tabu search approach to the non-identical parallel machines scheduling problem with sequence dependent setup times. IERC 03, The IIE Annual Conference, May 18-20, Portland, OR

Abstract:
We present a tabu search-based heuristic algorithm for the solution of the non-identical parallel machines scheduling problem with sequence-dependent setup times. The problem is an NP-hard and finding an optimal solution is unlikely in general. Consequently, heuristic techniques are appropriate for solving it. The criterion of interest in this work is the minimum makespan. The proposed algorithm uses two phases of perturbation in the search of better solutions. One phase (Intra-machine perturbation) optimizes the sequence of jobs on the machines, while the second (inter-machine perturbation) balances the assignment of the jobs to the machine. Structure of the algorithm and the tabu search concepts, are explained and defined. Computational results are reported.
Keywords: Scheduling, Non-identical, Parallel machines, setup times, tabu search

An Investigation of the Group Scheduling Heuristics in a Flow-Line Cell

Full Citation:
Huzayyin, A., Badr, M, Helal, M. 2000. An investigation of the group scheduling heuristics in a flow-line cell., Current Advances in Mechanical Design & Production; 7th Cairo University International MDP Conference, February 12-15, Cairo, Egypt.

Abstract
A comparative study of group scheduling (GS) in a flow line cell is presented. Three simple scheduling heuristics are compared with two iterative improvement heuristics. The objective is minimizing makespan and total flow time separately. A number of modifications are proposed in order to explore the performance of the heuristics and to investigate the characteristics of the GS model. In addition, a timetabling procedure for multi-family cells is proposed, considering the presence of the zero processing times. Results showed that the proposed modification could improve the performance of the heuristics under study. The iterative improvement techniques were found appropriate for GS not only because of their superiority over the simple methods but because they can handle the phases’ interaction in GS as well. The tabu search heuristic is found preferable to the simulated annealing heuristic.
Keywords: Group scheduling, Heuristics, Flow-line cell, Tabu search, Simulated annealing.