Batch Of Customers Research Articles

Optimized Configuration of Manufacturing Resources for Middle and Lower Batch Customization Enterprises in Cloud Manufacturing Environment

The optimal configuration of manufacturing resources in the cloud manufacturing environment has always been the focus of research on various advanced manufacturing systems. Aiming at the problem of manufacturing resources optimization configuration for middle and lower batch customization enterprises in cloud manufacturing environment, this paper gives a bi-level programming model for manufacturing resources optimization configuration in cloud manufacturing environment which fully considers customer satisfaction and enterprise customization economic benefits. The method firstly identifies the relationship between customer demands and customer satisfaction through questionnaires and quantifies the Kano model effectively. Then, it uses Quality Function Deployment (QFD) to transform customer demand characteristics into engineering characteristics and integrates the qualitative and quantitative results of the Kano model. Next, the method establishes enterprise economic benefits function according to the factors of order quantity and input cost. Furthermore, a comprehensive nonlinear bi-level programming model is established based on cost, time, and quality constraints. The model is solved by intelligent algorithm. Finally, the validity and feasibility of the model are verified by model simulation of actual orders of an enterprise. This method effectively realizes the optimal configuration of manufacturing resources in the cloud manufacturing environment, while maximizing the interests of both suppliers and demanders.

Tail asymptotics for a state-dependent bulk matching queueing system with impatient customers

We study a state-dependent bulk matching queueing system with impatient customers, where customers and servers visit the system from both sides. Servers provide services in a batch with a maximum size and take matching customers away instantly. To characterize such a queueing system, the corresponding Markov process is constructed by the number of complete batches of customers and the number of remaining customers in the incomplete batch. By analyzing this system, we find it difficult to obtain the joint stationary distribution of the Markov process. Therefore, we consider the tail asymptotics for the joint probabilities. Using the matrix analytic method and censoring technique, we obtain the one-term and general expansions for the nonzero elements of the rate matrices, where the coefficients of the expansions are presented in the closed form. On the basis of these expansion formulae, the exact tail asymptotic result for the joint stationary probabilities is derived.

Analysis of bulk queue with unreliable service station, second optional repair, N-policy multiple vacation, loss and immediate feedback in production system

In this paper an unreliable server bulk service queue with second optional repair, multiple vacation under N-policy, customer's feedback and impatience are considered. After finishing a service, the server avails a multiple vacation under N-policy only when the queue length is less than 'a'. Server vacation models are very much useful for a queueing system in which server needs to utilise his idle time for a different purpose. The server is subject to breakdown during the service and requires second optional repair for restoration. After repair completion, the server will start its remaining service to the batch of customers whose service was interrupted. Further, it is assumed that the arriving units may balk (loss) from the system when the server is on vacation and immediate feedback service was provided to the dissatisfied customers. The queue size distribution at a random and departure epoch has been derived using the supplementary variable technique. Finally, the stability condition, some performance measures, particular cases and numerical results of the proposed model are obtained.

Analysis of customer’s impatience on bulk service queueing system with unreliable server, setup time and two types of multiple vacation

In this investigation, we analyse the customer's impatience on unreliable bulk queueing system with two types of vacation. Depending upon the length of queue, the server is permitted to take two types of vacation called type I vacation and type II vacation. The server is possibly affected by breakdowns and takes considerable time for setup before the repair begins to start. After repair completion, the server will start its remaining service to the batch of customers whose service was interrupted. It could be assumed that the arriving units may be balked from the system when the server is on vacation (type I or type II). By incorporating the supplementary variables technique, the probability generating function of the queue size at an arbitrary and departure time epoch for the designed queueing system are derived. Finally, the stability condition, some performance measures, particular cases are obtained with appropriate numerical illustrations and graphical presentation.

Analysis of bulk queue with unreliable service station, second optional repair, N-policy multiple vacation, loss and immediate feedback in production system

In this paper an unreliable server bulk service queue with second optional repair, multiple vacation under N-policy, customer's feedback and impatience are considered. After finishing a service, the server avails a multiple vacation under N-policy only when the queue length is less than 'a'. Server vacation models are very much useful for a queueing system in which server needs to utilise his idle time for a different purpose. The server is subject to breakdown during the service and requires second optional repair for restoration. After repair completion, the server will start its remaining service to the batch of customers whose service was interrupted. Further, it is assumed that the arriving units may balk (loss) from the system when the server is on vacation and immediate feedback service was provided to the dissatisfied customers. The queue size distribution at a random and departure epoch has been derived using the supplementary variable technique. Finally, the stability condition, some performance measures, particular cases and numerical results of the proposed model are obtained.

Analysis of an Admission Control $$M^{[X]}/G(a,b)/1$$ Queue with Multiple Vacation, Restricted Re-service, Closedown and Setup Times

The objective of this paper is to analyze an $$M^{[X]}/G(a,b)/1$$ queueing model with admission control, multiple vacation, restricted re-service, setup and closedown times. At the moment of service completion, the leaving batch of customers may request for re-service with probability $$\eta $$ and it is not compulsory to accept the request. The server accepts the request with probability $$\zeta $$ and restricts it with probability $$1-\zeta $$ . All the batches of customers are not allowed all the time into the system. On completion of a service or re-service, if the queue length is $$\omega $$ , where $$\omega <a$$ , then the server resumes closedown work. After that, the server leaves for a vacation of random length. When the server returns from a vacation if the queue length is still less than a, he leaves for another vacation and so on until he finds at least a customers in the queue. If the queue length is at least a, then the server commences setup work before starting the service. Using supplementary variable technique, the steady-state probability generating function of the system size at an arbitrary time is obtained. The performance measures and cost model are also derived. Numerical illustrations are presented to visualize the effect of system parameters.

Deprecated in policy, abundant in market? The frugal innovation of Chinese low-speed EV industry

In the era of “Industry 4.0”, individualized demand and small batch customization manufacturing will become the trend, which calls for strong capabilities of customer orientation and rapid reaction. In addition to the redesign of smart and autonomous production processes, the market-oriented frugal innovation is a valuable exploration under the framework of “Industry 4.0”. This paper anchors itself at a deprecated policy context to study frugal innovation patterns and their forming mechanisms, which is still a rarely touched area. By selecting as its cases Shifeng, Baoya and Taiqi from the Shandong province, China, this paper uses a qualitative approach to analyze low-speed electric vehicle (EV) businesses according to a three-dimension frugal innovation framework composed by business ecosystem (BE) configurations, BE capabilities and innovation process. The findings are as follows, (1) there are three typical frugal innovation patterns, namely market-based persistence, market-based contingency and technology-based contingency, which help frugal innovators obtain an abundant market performance even under a deprecated policy environment; (2) a vertical integration network and strong marketing capabilities are the capital to select a market-based persistence pattern, while the lack of some substantial resources and capabilities compels firms to have to adopt a more flexible way of frugal innovation in order to carve out a safe niche. This paper contributes to frugal innovation research by exploring a new deprecated policy context rather than traditional institution voids, constructing a frugal innovation framework from the BE perspective by focusing on focal firms, and proposing three frugal innovation patterns under different resource constraints. From the practical side, this paper suggests that future innovation policy should balance advanced technology requirements and practical market demands, and the governments should also emphasize market positioning and demand orientation in the process of Industry 4.0 transformation.

On the optimal control of loss probability and profit in a GI/C-BMSP/1/N queueing system

This paper deals with a single server queueing system where the waiting space is limited. The server serves the customer in batches. The arrival process is considered to be renewal type and the services are considered to be correlated which has been presented by a continuous-time batch Markovian service process (C-BMSP). Distribution of the system length at pre-arrival instant of a customer and at an arbitrary-epoch have been determined for this queueing system. These probability distributions have been used for obtaining the blocking probability of an arbitrary customer, expected system-length, expected waiting time of an arbitrary customer in the system, and several other important performance measures. This model may find application in queueing systems involving inventory where delay in demand may lead to perishing of goods due to long wait in the system. Also, a profit function has been derived for such a queueing model to maximize the profit from the system for certain model parameters. Finally, assuming that the inter-arrival time follows phase-type distribution, a few numerical examples have been presented in the form of graphs and tables.

Manufacture and delivery scheduling for customers on one manufacturing machine with an availability constraint

We consider a scheduling problem with the joint consideration of manufacture and delivery for m customers in different locations. In the manufacture period, there must be some interrupted job because of the arranged maintenance of the machine, and that job can be resumable when the machine becomes available again. In the delivery period, amounts of vehicles without limits of load capacity deliver completed jobs belonging to the same customer to customers in batches. The cost of each delivery is proportional to the distance between the customer and the manufacturer. Our goal is to minimize the sum of total departure time and total delivery cost. The problem is solved optimally by a dynamic programming algorithm with polynomial time O(m2n4), where n is the number of all jobs.

On a batch matching system with impatient servers and boundedly rational customers

In this paper we consider a batch matching system with impatient servers and boundedly rational customers, which is essentially a double-ended batch service system. Each server is responsible for a batch of customers and serves them instantaneously. Especially, we assume that the servers have the characteristic of ”impatience”, which will lead to incomplete batch processing of each service. To derive the stationary distribution of system states, we combine two methods (called probability generating function method and G-matrix method), and some main performance measures are captured. In addition, we assume the customers are boundedly rational, that is, they are unable to estimate their sojourn times and utilities accurately. To deal, a logit model is employed to model this characteristic of the customers, and by which, we obtain the customers’ equilibrium joining fraction which is compared with the equilibrium joining probability of fully rational customers afterwards. Depending on whether the service is visible or invisible, we conduct some numerical analyses to show main parameters’ impact on equilibrium fraction, along with some intuitive explanations. Finally, to make the system viable economically, a function of service provider’s utility is developed and several numerical plots are presented to study the impact of several main parameters on the utility. Through the PSO (Particle Swarm Optimization) algorithm, we numerically obtain the maximum utility point within a certain range of multiple parameters.

Permutation Flow Shop Scheduling With Batch Delivery to Multiple Customers in Supply Chains

Rapid changes in production environments have motivated researchers and industrial manufacturers to coordinate the production and distribution in supply chain management. This paper aims to address the permutation flow shop scheduling problem with batch delivery to multiple customers. In this problem, products are first manufactured in a permutation flow shop, and subsequently delivered to multiple customers in batches. To optimize the tradeoff between customer service and distribution cost, the objective of this paper is to minimize the total cost of tardiness and batch delivery. To deal with such optimization problem, two simple heuristics and a novel meta-heuristic (GA-TVNS) are developed to determine integrated production and distribution schedules. GA-TVNS hybridizes genetic algorithm and variable neighborhood search (VNS) to provide better exploration and exploitation in the search space. Moreover, to improve the local search of VNS, two new learning-based neighborhood structures are designed based on the classical school learning process of teaching–learning-based optimization. Computation experiments on both small-sized and large-sized test problems indicate that GA-TVNS performs the best among all the compared scheduling algorithms.

Analysis of a single server batch arrival unreliable queue with balking and general retrial time

ABSTRACTThis paper deals with a batch arrivals queue with general retrial time, breakdowns, repairs and reserved time. Here we assume that customers arrive according to compound Poisson processes. Any arriving batch of primary customers finds the server free, one of the customers from the batch enters into the service area and the rest of them join into the orbit. The primary customers who find the server busy or failed are allowed to balk or are queued in the orbit in accordance with FCFS retrial policy. The customer whose service is interrupted can stay at the server waiting for repair or enter into service orbit. After the repair is completed, the server resumes service immediately if the customer in service has remained in the service position. This model has a potential applications in various fields, such as in the cognitive radio network and the manufacturing systems. By using supplementary variables technique, we carry out an extensive analysis of the considered model. Then, we obtain some important performance measures, stochastic decomposition property of the system size distribution and the reliability indices. Next, by setting the appropriate parameters, some special cases are discussed. Finally, some numerical examples and cost analysis are presented.

Performance characteristics of a batch service queueing system with functioning server failure and multiple vacations

This paper examines bulk arrival and batch service queueing system with functioning server failure and multiple vacations. Customers are arriving into the system in bulk according to Poisson process with rate λ. Arriving customers are served in batches with minimum of ‘a’ and maximum of ‘b’ number of customers according to general bulk service rule. In the service completion epoch if the queue length is less than ‘a’ then the server leaves for vacation (secondary job) of random length. After a vacation completion, if the queue length is still less than ‘a’ then the server leaves for another vacation. The server keeps on going vacation until the queue length reaches the value ‘a’. The server is not stable at all the times. Sometimes it may fails during functioning of customers. Though the server fails service process will not be interrupted.It will be continued for the current batch of customers with lower service rate than the regular service rate. The server will be repaired after the service completion with lower service rate. The probability generating function of the queue size at an arbitrary time epoch will be obtained for the modelled queueing system by using supplementary variable technique. Moreover various performance characteristics will also be derived with suitable numerical illustrations.

Scheduling with job delivery coordination on single machine

This paper investigates a single machine scheduling problem with job delivery coordination, in which each job demands different amount of storage space during transportation. In this problem, a set of independent jobs from a customer must first be processed on a machine without preemption and then delivered by two homogeneous vehicles to the customer in batches. To minimize the makespan, we develop a best possible polynomial-time heuristic with a worst-case ratio of 2.

Analysis of an MAP/PH/1 Queue with Flexible Group Service

AbstractA novel customer batch service discipline for a single server queue is introduced and analyzed. Service to customers is offered in batches of a certain size. If the number of customers in the system at the service completion moment is less than this size, the server does not start the next service until the number of customers in the system reaches this size or a random limitation of the idle time of the server expires, whichever occurs first. Customers arrive according to a Markovian arrival process. An individual customer’s service time has a phase-type distribution. The service time of a batch is defined as the maximum of the individual service times of the customers which form the batch. The dynamics of such a system are described by a multi-dimensional Markov chain. An ergodicity condition for this Markov chain is derived, a stationary probability distribution of the states is computed, and formulas for the main performance measures of the system are provided. The Laplace–Stieltjes transform of the waiting time is obtained. Results are numerically illustrated.

A Geo[X]/G[X]/1 retrial queueing system with removal work and total renewal discipline

In this paper we consider a discrete-time retrial queueing system with batch arrivals of geometric type and general batch services. The arriving group of customers can decide to go directly to the server expelling out of the system the batch of customers that is currently being served, if any, or to join the orbit. After a successful retrial all the customers in the orbit get service simultaneously. An extensive analysis of the model is carried out, and using a generating functions approach some performance measures of the model, such as the first distribution’s moments of the number of customers in the orbit and in the system, are obtained. The generating functions of the sojourn time of a customer in the orbit and in the system are also given. Finally, in the section of conclusions and research results the main contributions of the paper are commented.

Order acceptance and scheduling with batch delivery

We study an order acceptance and scheduling problem with batch delivery in a supply chain consisting of a manufacturer and a customer. The manufacturer can rejects some orders placed by the customer, and processes the others on parallel machines and then delivers them to the customer in batches. The objective is to minimize the weighted sum of the maximum lead time of the accepted orders and the total cost of rejecting and delivering orders. We develop two approximation algorithms for this NP-hard problem.

The analysis of batch sojourn-times in polling systems

We consider a cyclic polling system with general service times, general switch-over times, and simultaneous batch arrivals. This means that at an arrival epoch, a batch of customers may arrive simultaneously at the different queues of the system. For the exhaustive service discipline, we study the batch sojourn-time, which is defined as the time from an arrival epoch until service completion of the last customer in the batch. We obtain exact expressions for the Laplace–Stieltjes transform of the steady-state batch sojourn-time distribution, which can be used to determine the moments of the batch sojourn-time and, in particular, its mean. However, we also provide an alternative, more efficient way to determine the mean batch sojourn-time, using mean value analysis. We briefly show how our framework can be applied to other service disciplines: locally gated and globally gated. Finally, we compare the batch sojourn-times for different service disciplines in several numerical examples. Our results show that the best performing service discipline, in terms of minimizing the batch sojourn-time, depends on system characteristics.

Performance analysis of an M&lt;SUP align="right"&gt;x&lt;/SUP&gt;/G/1 feedback retrial queue with non-persistent customers and multiple vacations with N-policy

This paper is concerned with the analysis of an Mx/G/1 feedback retrial queue with non-persistent customers and multiple vacations with N-policy. If an arriving batch of customers finds the server idle, one of the arriving customers starts its service immediately and the rest joins a retrial group. Otherwise, if an arriving batch of customers on arrival finds the server busy, becomes impatient and leaves the system with probability (1 - α) and with probability α, they enter into the orbit. At a service completion epoch, if the number of customers in the orbit is zero, the server does a secondary job (vacation) repeatedly until the retrial group size reaches N. At the secondary job completion epoch, if the orbit size is at least N, then the server remains in the system to render service for customers from main pool or from retrial group. At a service completion epoch, the leaving customer may either request for another service with probability f or leave the system forever with probability d (where f + d = 1).

Performance analysis of an M&lt;SUP align="right"&gt;x&lt;/SUP&gt;/G/1 feedback retrial queue with non-persistent customers and multiple vacations with N-policy

This paper is concerned with the analysis of an Mx/G/1 feedback retrial queue with non-persistent customers and multiple vacations with N-policy. If an arriving batch of customers finds the server idle, one of the arriving customers starts its service immediately and the rest joins a retrial group. Otherwise, if an arriving batch of customers on arrival finds the server busy, becomes impatient and leaves the system with probability (1 - α) and with probability α, they enter into the orbit. At a service completion epoch, if the number of customers in the orbit is zero, the server does a secondary job (vacation) repeatedly until the retrial group size reaches N. At the secondary job completion epoch, if the orbit size is at least N, then the server remains in the system to render service for customers from main pool or from retrial group. At a service completion epoch, the leaving customer may either request for another service with probability f or leave the system forever with probability d (where f + d = 1).