Service Rate Optimization of Manufacturing Cell Based on Cost Models

2011 ◽  
Vol 314-316 ◽  
pp. 2055-2059
Author(s):  
Yan Yan Zhang ◽  
Cheng Su ◽  
Yong Shang ◽  
Zhong Xue Li
Keyword(s):  
Queuing Theory ◽  
Design Method ◽  
Cost Model ◽  
Service Rate ◽  
Cost Models ◽  
Expected Cost ◽  
Manufacturing Cell ◽  
Service Rates ◽  
Traditional Manufacturing ◽  
Rate Optimization

Since most traditional manufacturing cell design methods and some involved algorithms developed in the past few years always investigate the selection and arrangement of equipment during the design process, this paper describes a new methodology focusing on optimizing the service rates of the manufacturing cell under developing. At first, the expected cost model based on queuing theory of each process in a manufacturing cell is developed and then the optimal service rates of the equipment that make the cost the least could be obtained. Next, the designer can choose the facilities according to these parameters to configure a new manufacturing cell whose total expected cost is optimal. Finally, a numerical example is used to illustrate the advantage and validity of the new design method.

scholarly journals Service Rate Optimization of Finite Population Queueing Model with State Dependent Arrival and Service Rates

2018 ◽  
Vol 13 (1) ◽  
pp. 60-68
Author(s):  
Sushil Ghimire ◽  
Gyan Bahadur Thapa ◽  
Ram Prasad Ghimire
Keyword(s):  
Finite Population ◽  
Arrival Rate ◽  
Service Rate ◽  
Queueing Model ◽  
State Dependent ◽  
Service Rates ◽  
Rate Optimization

 Providing service immediately after the arrival is rarely been used in practice. But there are some situations for which servers are more than the arrivals and no one has to wait to get served. In this model, arrival rate is

Optimization of Queuing Theory Based on Vague Environment

2016 ◽  
Vol 5 (1) ◽  
pp. 1-26 ◽  
Author(s):  
Verónica Andrea González-López ◽  
Ramin Gholizadeh ◽  
Aliakbar M. Shirazi
Keyword(s):  
Everyday Life ◽  
Real World ◽  
Queuing Theory ◽  
Arrival Rate ◽  
Service Rate ◽  
New Approach ◽  
The Real ◽  
Processing Times ◽  
Queuing Models ◽  
Service Rates

Waiting lines or queues are commonly occurred both in everyday life and in a variety of business and industrial situations. The various arrival rates, service rates and processing times of jobs/tasks usually assumed are exact. However, the real world is complex and the complexity is due to the uncertainty. The queuing theory by using vague environment is described in this paper. To illustrate, the approach analytical results for M/M/1/8 and M/M/s/8 systems are presented. It optimizes queuing models such that the arrival rate and service rate are vague numbers. This paper results a new approach for queuing models in the vague environment that it can be more effective than deterministic queuing models. A numerical example is illustrated to check the validity of the proposed method.

ANALYSIS OF A BULK QUEUE WITH FAST AND SLOW SERVICE RATES AND MULTIPLE VACATIONS

2005 ◽  
Vol 22 (02) ◽  
pp. 239-260 ◽  
Author(s):  
R. ARUMUGANATHAN ◽  
K. S. RAMASWAMI
Keyword(s):  
Performance Measures ◽  
Queue Length ◽  
Queueing System ◽  
Cost Model ◽  
Probability Generating Function ◽  
Service Rate ◽  
Multiple Vacations ◽  
Bulk Queue ◽  
Service Rates ◽  
Number Of Customers

We analyze a Mx/G(a,b)/1 queueing system with fast and slow service rates and multiple vacations. The server does the service with a faster rate or a slower rate based on the queue length. At a service completion epoch (or) at a vacation completion epoch if the number of customers waiting in the queue is greater than or equal to N (N > b), then the service is rendered at a faster rate, otherwise with a slower service rate. After finishing a service, if the queue length is less than 'a' the server leaves for a vacation of random length. When he returns from the vacation, if the queue length is still less than 'a' he leaves for another vacation and so on until he finally finds atleast 'a' customers waiting for service. After a service (or) a vacation, if the server finds atleast 'a' customers waiting for service say ξ, then he serves a batch of min (ξ, b) customers, where b ≥ a. We derive the probability generating function of the queue size at an arbitrary time. Various performance measures are obtained. A cost model is discussed with a numerical solution.

Introducing Likelihood of Occurrence and Expected Cost to Human Error and Functional Failure Reasoning Framework

2020 ◽  
Author(s):  
Lukman Irshad ◽  
Daniel Hulse ◽  
H. Onan Demirel ◽  
Irem Y. Tumer ◽  
David C. Jensen
Keyword(s):  
Human Error ◽  
Cost Model ◽  
Critical Event ◽  
Cost Models ◽  
Worst Case ◽  
Expected Cost ◽  
Human Errors ◽  
Functional Failure ◽  
System Risk ◽  
Component Failures

Abstract Risk-based design uses severity and occurrence quantification to determine overall system risk and prioritize the most important hazards. To fully understand and effectively mitigate potential risks, the effects of component failures and human errors (acting alone and in tandem) need to be considered early. Then one can determine whether to allocate resources to proactively mitigate human errors in the design process. In previous work, the Human Error and Functional Failure Reasoning (HEFFR) framework was developed to model effects of human errors and component failures in a system, taking critical event scenarios as inputs and producing functional failures, human errors, and their propagation paths as outputs. With automated scenario generation, this framework can model millions of scenarios that cause system critical functions to fail. However, the outputs of this framework do not include any quantifiable measures to assess the risk of the hazards or prioritize fault scenarios. This work addresses these shortcomings by using a scenario probability and cost model to quantify the expected cost of failures in the HEFFR framework. A coolant tank case study is used to demonstrate this approach. The results show that the quantifiable measures enable HEFFR to identify worst-case scenarios, prioritize scenarios with the highest impact, and improve human-product interactions. However, the underlying likelihood and cost models are subject to uncertainties which may affect the assessments.

An QPSL Queuing Model for Load Balancing in Cloud Computing

2020 ◽  
Vol 16 (3) ◽  
pp. 33-48
Author(s):  
Shadab Siddiqui ◽  
Manuj Darbari ◽  
Diwakar Yagyasen
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Queuing Theory ◽  
Service Rate ◽  
Queuing Model ◽  
Queuing Models ◽  
Fifo Queue ◽  
Queue Discipline ◽  
Service Rates ◽  
Waiting Lines

Load balancing is the process of distributing a workload among various servers. Queuing is the most common scenario for day-to-day applications. Queuing theory is used to study the problem of waiting lines. Queuing theory bridges the gap between service demands and the delay in replies given to users. The proposed QPSL Queuing Model makes use of M/M/k queue with FIFO queue discipline for load balancing in cloud computing. The model makes use of exponential distribution for calculating service rates and Poisson distribution for calculating waiting lines. The proposed QPSL queuing model is also compared with other existing queuing models for load balancing on various parameters. The experimental analysis depicts that QPSL model performed better in terms of service rate and response time.

scholarly journals A Taylor Series Approach for Service-Coupled Queueing Systems with Intermediate Load

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Ekaterina Evdokimova ◽  
Sabine Wittevrongel ◽  
Dieter Fiems
Keyword(s):  
Performance Measures ◽  
Queueing Systems ◽  
Poisson Processes ◽  
Series Expansions ◽  
Service Rate ◽  
Single Server ◽  
Queueing Model ◽  
State Space Explosion ◽  
Finite Queues ◽  
Service Rates

This paper investigates the performance of a queueing model with multiple finite queues and a single server. Departures from the queues are synchronised or coupled which means that a service completion leads to a departure in every queue and that service is temporarily interrupted whenever any of the queues is empty. We focus on the numerical analysis of this queueing model in a Markovian setting: the arrivals in the different queues constitute Poisson processes and the service times are exponentially distributed. Taking into account the state space explosion problem associated with multidimensional Markov processes, we calculate the terms in the series expansion in the service rate of the stationary distribution of the Markov chain as well as various performance measures when the system is (i) overloaded and (ii) under intermediate load. Our numerical results reveal that, by calculating the series expansions of performance measures around a few service rates, we get accurate estimates of various performance measures once the load is above 40% to 50%.

Analysis of separable Markov-modulated rate models for information-handling systems

1991 ◽  
Vol 23 (01) ◽  
pp. 105-139 ◽  
Author(s):  
Thomas E. Stern ◽  
Anwar I. Elwalid
Keyword(s):  
Solution Technique ◽  
Service Rate ◽  
Processing Unit ◽  
Equilibrium Equations ◽  
Flow Models ◽  
Separability Property ◽  
Finite State ◽  
Service Rates ◽  
Rate Processes ◽  
Markov Modulated

In many communication and computer systems, information arrives to a multiplexer, switch or information processor at a rate which fluctuates randomly, often with a high degree of correlation in time. The information is buffered for service (the server typically being a communication channel or processing unit) and the service rate may also vary randomly. Accurate capture of the statistical properties of these fluctuations is facilitated by modeling the arrival and service rates as superpositions of a number of independent finite state reversible Markov processes. We call such models separable Markov-modulated rate processes (MMRP). In this work a general mathematical model for separable MMRPs is presented, focusing on Markov-modulated continuous flow models. An efficient procedure for analyzing their performance is derived. It is shown that the ‘state explosion' problem typical of systems composed of a large number of subsystems, can be circumvented because of the separability property, which permits a decomposition of the equations for the equilibrium probabilities of these systems. The decomposition technique (generalizing a method proposed by Kosten) leads to a solution of the equilibrium equations expressed as a sum of terms in Kronecker product form. A key consequence of decomposition is that the computational complexity of the problem is vastly reduced for large systems. Examples are presented to illustrate the power of the solution technique.

scholarly journals GASOL: Gas Analysis and Optimization for Ethereum Smart Contracts

2020 ◽  
pp. 118-125 ◽  
Author(s):  
Elvira Albert ◽  
Jesús Correas ◽  
Pablo Gordillo ◽  
Guillermo Román-Díez ◽  
Albert Rubio
Keyword(s):  
Upper Bound ◽  
Cost Model ◽  
Gas Analysis ◽  
Smart Contracts ◽  
Cost Models ◽  
Automatic Optimization ◽  
Gas Consumption ◽  
The Cost ◽  
Storage Patterns ◽  
Program Line

Abstract We present the main concepts, components, and usage of Gasol, a Gas AnalysiS and Optimization tooL for Ethereum smart contracts. Gasol offers a wide variety of cost models that allow inferring the gas consumption associated to selected types of EVM instructions and/or inferring the number of times that such types of bytecode instructions are executed. Among others, we have cost models to measure only storage opcodes, to measure a selected family of gas-consumption opcodes following the Ethereum’s classification, to estimate the cost of a selected program line, etc. After choosing the desired cost model and the function of interest, Gasol returns to the user an upper bound of the cost for this function. As the gas consumption is often dominated by the instructions that access the storage, Gasol uses the gas analysis to detect under-optimized storage patterns, and includes an (optional) automatic optimization of the selected function. Our tool can be used within an Eclipse plugin for which displays the gas and instructions bounds and, when applicable, the gas-optimized function.

scholarly journals Performance Modelling of Health-care Service Delivery in Adekunle Ajasin University, Akungba-Akoko, Nigeria Using Queuing Theory

2020 ◽  
pp. 119-127
Author(s):  
Orimoloye Segun Michael
Keyword(s):  
Health Care ◽  
Service Delivery ◽  
Queuing Theory ◽  
Health Care Service ◽  
Health Centre ◽  
Arrival Rate ◽  
Queuing System ◽  
Service Rate ◽  
Suitable Model ◽  
The Mean

The queuing theory is the mathematical approach to the analysis of waiting lines in any setting where arrivals rate of the subject is faster than the system can handle. It is applicable to the health care setting where the systems have excess capacity to accommodate random variation. Therefore, the purpose of this study was to determine the waiting, arrival and service times of patients at AAUA Health- setting and to model a suitable queuing system by using simulation technique to validate the model. This study was conducted at AAUA Health- Centre Akungba Akoko. It employed analytical and simulation methods to develop a suitable model. The collection of waiting time for this study was based on the arrival rate and service rate of patients at the Outpatient Centre. The data was calculated and analyzed using Microsoft Excel. Based on the analyzed data, the queuing system of the patient current situation was modelled and simulated using the PYTHON software. The result obtained from the simulation model showed that the mean arrival rate of patients on Friday week1 was lesser than the mean service rate of patients (i.e. 5.33> 5.625 (λ > µ). What this means is that the waiting line would be formed which would increase indefinitely; the service facility would always be busy. The analysis of the entire system of the AAUA health centre showed that queue length increases when the system is very busy. This work therefore evaluated and predicted the system performance of AAUA Health-Centre in terms of service delivery and propose solutions on needed resources to improve the quality of service offered to the patients visiting this health centre.

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