Mohd Kamal Mohd Nawawi

A Discrete Event Simulation Model for Evaluating the Performances of an M/G/C/C State Dependent Queuing System

M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed.

Knowledge-Based Collaborative Lean Manufacturing Management (KBCLMM) System

Knowledge-Based Collaborative Lean Manufacturing Management (KBCLMM) System The objective of this research paper is to demonstrate the application of hybrid Knowledge-Based System, Gauging Absences of Pre-Requisites (GAP), and Analytic Hierarchy Process (AHP) approaches for selecting the improvement programs for Collaborative Lean Manufacturing Management (CLMM) System. In this research, a generic Knowledge-Based System is developed to measure the level of CLMM adoption in automotive manufacturers compared to the ideal system. Using the embedded GAP and AHP technique, the key lean manufacturing improvement programs can be prioritised by using both qualitative and quantitative criteria. The analysis covers the planning stage of the KBCLMM. The utilisation of the approach is demonstrated with an illustrative example. System Zespołowego Zarządzania Produkcją, Obniżający Nakłady, Oparty na Bazie Wiedzy Celem niniejszej pracy badawczej jest przedstawienie rozmaitych sposobów wyboru programów poprawy wydajności dla systemu Zespołowego Zarządzania Produkcją obniżającego nakłady (CLMM), opartego na Bazach Wiedzy. Omawiane sposoby, to Pomiar Niedostępności Warunków Wstępnych (Gauging Absences of Pre-Requisites - GAP) oraz Analityczne Procesy Hierarchiczne (Analytic Hierarchy Process - AHP). W ramach prezentowanej pracy badawczej opracowano generyczny System Oparty na Bazie Wiedzy pozwalający na pomiar przydatności systemu CLMM w zakładzie produkcyjnym przemysłu samochodowego w porównaniu z systemem idealnym. Dzięki zastosowaniu wbudowanych technik GAP oraz AHP można optymalizować kluczowe programy zarządzania produkcją, określając priorytety za pomocą kryteriów ilościowych, jak i jakościowych. Analiza obejmuje również etap planowania systemu KBCLMM. Wykorzystanie każdego sposobu jest przedstawione za pomocą poglądowego przykładu.

Analytic network process model for sustainable lean and green manufacturing performance indicator

Sustainable manufacturing is regarded as the most complex manufacturing paradigm to date as it holds the widest scope of requirements. In addition, its three major pillars of economic, environment and society though distinct, have some overlapping among each of its elements. Even though the concept of sustainability is not new, the development of the performance indicator still needs a lot of improvement due to its multifaceted nature, which requires integrated approach to solve the problem. This paper proposed the best combination of criteria en route a robust sustainable manufacturing performance indicator formation via Analytic Network Process (ANP). The integrated lean, green and sustainable ANP model can be used to comprehend the complex decision system of the sustainability assessment. The finding shows that green manufacturing is more sustainable than lean manufacturing. It also illustrates that procurement practice is the most important criteria in the sustainable manufacturing performance indicator.

Assessing the responses of physical parameters in ocean via statistical approach

It is essential to assess a physical parameter in response to the changes in other physical parameter. Exploration on the type of relationship between two physical parameters depends on models and expert view due to the complexity of the ecosystems. These need validation with actual data over a certain periods. Innovative statistical approaches, particularly the nonparametric regression is presented to investigate the ecological relationships. These are achieved by demonstrating the features of salinity, conductivity and temperature at a sampling point in Selat Tebrau. Observed data monitored for 10 years from 2004–2013 are examined. Testing for no-effect and linearity for salinity and temperature; log conductivity and temperature, and log conductivity and salinity, with the ecological objectives of investigating the evidence of changes in each of the above physical parameter. The results show the appropriateness of smooth function to explain the variation of salinity in response to the changes in tempera...

Planning and design of a knowledge based system for green manufacturing management

This paper presents a conceptual design approach to the development of a hybrid Knowledge Based (KB) system for Green Manufacturing Management (GMM) at the planning and design stages. The research concentrates on the GMM by using a hybrid KB system, which is a blend of KB system and Gauging Absences of Pre-requisites (GAP). The hybrid KB/GAP system identifies all potentials elements of green manufacturing management issues throughout the development of this system. The KB system used in the planning and design stages analyses the gap between the existing and the benchmark organizations for an effective implementation through the GAP analysis technique. The proposed KBGMM model at the design stage explores two components, namely Competitive Priority and Lean Environment modules. Through the simulated results, the KBGMM System has identified, for each modules and sub-module, the problem categories in a prioritized manner. The System finalized all the Bad Points (BP) that need to be improved to achieve benchmark implementation of GMM at the design stage. The System provides valuable decision making information for the planning and design a GMM in term of business organization.

Queuing network approach for building evacuation planning

The complex behavior of pedestrians in a limited space layout can explicitly be modeled using an M/G/C/C state dependent queuing network. This paper implements the approach to study pedestrian flows through various corridors in a topological network. The best arrival rates and their impacts to the corridors’ performances in terms of the throughput, blocking probability, expected number of occupants in the system and expected travel time were first measured using the M/G/C/C analytical model. These best arrival rates were then fed to its Network Flow Programming model to find the best arrival rates to source corridors and routes optimizing the network’s total throughput. The analytical results were then validated using a simulation model. Various results of this study can be used to support the current Standard Operating Procedures (SOP) to efficiently and safely evacuate people in emergency cases.

Modeling of Aircraft Composite Parts Using Simulation

Simulation is one of the most powerful tools available for decision makers to study, analyze and evaluate any design and operation particularly for complex processes and systems. One of the largest application areas for simulation modelling is the manufacturing systems. As such, it is widely applied in manufacturing as a representation of the industrial operation systems allowing the systems to be observed, learnt and tested in a more holistic manner. This paper is based on a preliminary study that demonstrates the application of computer simulation modelling, which is a branch of Operations Research techniques, as a means to identify bottlenecks in order to determine the ideal operating conditions for large scale aircraft composite parts production plant in Malaysia. The model development of the plant under study was built using Arena software.

Developing a discrete event simulation model for university student shuttle buses

Providing shuttle buses for university students to attend their classes is crucial, especially when their number is large and the distances between their classes and residential halls are far. These factors, in addition to the non-optimal current bus services, typically require the students to wait longer which eventually opens a space for them to complain. To considerably reduce the waiting time, providing the optimal number of buses to transport them from location to location and the effective route schedules to fulfil the students’ demand at relevant time ranges are thus important. The optimal bus number and schedules are to be determined and tested using a flexible decision platform. This paper thus models the current services of student shuttle buses in a university using a Discrete Event Simulation approach. The model can flexibly simulate whatever changes configured to the current system and report its effects to the performance measures. How the model was conceptualized and formulated for future s...

Green supply chain: Simulating road traffic congestion

With the increasing awareness of the consumers about environmental issues, businesses, households and governments increasingly want use green products and services which lead to green supply chain. This paper discusses a simulation study of a selected road traffic system that will contribute to the air pollution if in the congestion state. Road traffic congestion (RTC) can be caused by a temporary obstruction, a permanent capacity bottleneck in the network itself, and stochastic fluctuation in demand within a particular sector of the network, leading to spillback and queue propagation. A discrete-event simulation model is developed to represent the real traffic light control (TLC) system condition during peak hours. Certain performance measures such as average waiting time and queue length were measured using the simulation model. Existing system uses pre-set cycle time to control the light changes which is fixed time cycle. In this research, we test several other combination of pre-set cycle time with the objective to find the best system. In addition, we plan to use a combination of the pre-set cycle time and a proximity sensor which have the authority to manipulate the cycle time of the lights. The sensors work in such situation when the street seems to have less occupied vehicles, obviously it may not need a normal cycle for green light, and automatically change the cycle to street where vehicle is present.

A two stage data envelopment analysis model with undesirable output

The dependent relationship among the decision making units (DMU) is usually assumed to be non-existent in the development of Data Envelopment Analysis (DEA) model. The dependency can be represented by the multi-stage DEA model, where the outputs from the precedent stage will be the inputs for the latter stage. The multi-stage DEA model evaluate both the efficiency score for each stages and the overall efficiency of the whole process. The existing multi stage DEA models do not focus on the integration with the undesirable output, in which the higher input will generate lower output unlike the normal desirable output. This research attempts to address the inclusion of such undesirable output and investigate the theoretical implication and potential application towards the development of multi-stage DEA model.