Evaluating and Selecting Simulation Software Using the Analytic Hierarchy Process

Abstract

In order to be competitive and progress to a state of excellence in manufacture, companies are currently experiencing change. Decisions have to be made about the best way forward, and some insight into the possible outcomes is desirable. There is a small but growing awareness among British manufacturing companies that simulation could aid this insight, but potential users face the problem of evaluating and selecting from the many proprietary systems, the one which best matches their requirements at some preferred cost. Selection is made more difficult by continual updates and modifications to systems and by new software suppliers entering the market. Uses a research case study as the vehicle for proposing a framework for assessment and selection of simulation systems involving the use of the Analytic Hierarchy Process (AHP). Illustrates how this technique was used to make a system selection which matched a company′s selection criteria.

On Just-In-Time Production Leveling

“…Indeed, the lack of manufacturing archetypes to model building seems one of the most remarkable weakness for most simulator tools, since their presence could simplify the model development process for who speak the "language of business" [62]. Moreover, commercial simulators show several limitations if used to test custom heuristics, for example to level a JIT production or to solve a line-balancing problem: some authors report typical weaknesses in presenting the simulation output [63] or limited functionalities in terms of statistical analysis [64], on top of the lack of user-friendliness. For instance, most common commercial simulation software do not embed the most useful random distributions for manufacturing system analysis, such as the Weibull, Beta and Poisson distribution.…”

A Problem Solving Perspective on Evaluating Knowledge Management Technologies: Using Fuzzy Linear Programming Technique for Multiattribute Group Decision Making with Fuzzy Decision Variables

“…Cost is a common factor influencing the purchaser to choose the software [6]. It is simply the expenditure associated with KMS and includes product, license, training, maintenance and software subscription costs.…”

Simulación asistida por agentes para sistemas de fabricación inteligentes.

“…Algunos investigadores tal como Banks (Banks 1991, Banks, Aviles, McLaughlin & Yuan 1991, Banks 1996, Banks et al 2001), Breedam (Breedam, Raes & Velde 1990), Davis (Davis & Williams 1994), Holder (Holder 1990), Kochlar (Kochhar 1989), Law (Law & Haider 1989, Law & Kelton 1991, A.M.Law & McGomas 1992, Mackulak (Mackulak, Savory & Cochran 1994), Hlupic (Hlupic 1997, Hlupic & Paul 1995a, Hlupic & Paul 1995b), Kuljis (Kuljis 1996), Nikoukaran (Nikoukaran, Hulpic & Paul 1999), y Baldwin et al (Baldwin, Eldabi, Hlupic & Irani 2000) han propuesto varios criterios para la evaluación de programas de simulación desde distintos puntos de vista y niveles de abstracción.…”

“…Entre las procedimientos propuestos para dicha evaluación se incluye asignación de valores y su normalización para asignar una puntuación, para asignar una categoría (Banks 1996). Davis y Adams incluyen además del uso de dicha puntuación, un proceso analíti-co de jerarquía para identificar el mejor puntuado (Davis & Williams 1994). Otros tales como Hlupic y Paul en cambio, realizan la puntuación estimando la calidad de los simuladores, donde un 1 representa una calidad muy baja o ausencia de las característica, mientras que el 10 representa una calidad excelente (Hlupic & Paul 1995b).…”

“…Los criterios varían en cuanto al agrupamiento de característi-cas, ya que depende del nivel de abstracción elegido para la evaluación. Entre las criterios más representativos podemos mencionar el de Law y Haider (Law & Haider 1989), Law y McComas (Law & McComas 1999), Kochhar (Kochhar 1989), Holder (Holder 1990), Breedam et al (Breedam et al 1990), Banks et al (Banks et al 1991) , Kelton y Law (Law & Kelton 1991), Davis y Wiliams (Davis & Williams 1994), Banks (Banks 1996) y Maklulak (Mackulak et al 1994). Nikoukaran en su interés por proponer una visión más amplia con respecto a las características ideales para una herramienta de simulación, agrupa los criterios propuestos por dichos investigadores haciendoénfasis en aquellas en las que coinciden ) y Banks et al(Banks et al 2001.…”