Liang Zhang

Dr. Liang Zhang


Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 July 2012 in IEEE Transactions on Automation Science and Engineering
Verified
Journal Article
Closed access
GCGuorong Chen
Guorong Chen
LZLiang Zhang
Liang Zhang
JAJorge Arinez
Jorge Arinez
SBStephan Biller
Stephan Biller
Control of production operations is considered as one of the most economical methods to improve energy efficiency in manufacturing systems. This paper investigates energy consumption reduction in production systems through effective scheduling of machine startup and shutdown. Specifically, we consider serial production lines with finite buffers and machines having Bernoulli reliability model. This machine reliability model is applicable in production situations, where the downtime is relatively short and comparable to machine cycle time (e.g., automotive paint shops and general assembly). In this paper, using transient analysis of the systems at hand, an analytical performance evaluation technique is developed for Bernoulli serial lines with time-dependent machine efficiencies. In addition, tradeoff between productivity and energy-efficiency in production systems is discussed and the energy-efficient production problem is formulated as a constrained optimization problem. The effects and practical implications of operations schedule are demonstrated using a numerical study on automotive paint shop operations. Note to Practitioners - This paper develops an effective analytical tool to evaluate the performance of production systems with time-varying parameters of machine reliability. Using this tool, production engineers and managers can predict the performance of the production systems in real-time with high accuracy. In addition, based on this tool, production operators can determine the machine startup and shutdown schedule based on the current status of the line and production requirement. Numerical experiments show that significant energy savings can be obtained by applying effective machine operations schedule.

1 October 2006 in Computers & Operations Research
Verified
Journal Article
Closed access
LWLing Wang
Ling Wang
LZLiang Zhang
Liang Zhang
DZDa-Zhong Zheng
Da-Zhong Zheng

24 August 2018 in IEEE Transactions on Smart Grid
Verified
Journal Article
Closed access
Weiji HanWeiji Han
Weiji Han
Changfu ZouChangfu Zou
Changfu Zou
CZChen Zhou
Chen Zhou
LZLiang Zhang
Liang Zhang
Large-scale battery systems have been applied to a number of grid-level energy storage services such as microgrid capability and distribution upgrade due to the penetration of solar/wind energy. In these battery applications, charge imbalance among battery cells/modules/packs becomes a common issue, which can reduce available battery capacity, accelerate battery degradation, and even cause some safety hazards. To tackle this issue, various battery charge equalization (BCE) systems have been proposed in recent decades, among which the module-based BCE system is widely viewed as a promising solution and has drawn increasing attention. In this paper, we study the module-based BCE systems by presenting a mathematical model that can characterize the charge transfer behavior in such systems, and then proposes computationally efficient algorithms to estimate the instantaneous battery cell state of charge (SOC), charge equalization time, and charging/discharging time, based on given system parameters and various initial battery cell SOCs. In addition, the conditions are derived to ensure that all battery cells can reach charge equalization and then get fully charged/discharged together without overcharging/overdischarging. All theoretical results are illustrated and justified through extensive numerical experiments.

8 January 2008 in IIE Transactions
Verified
Journal Article
Open access
SMSemyon M. Meerkov
Semyon M. Meerkov
LZLiang Zhang
Liang Zhang
The steady-state performance of production systems with unreliable machines has been analyzed extensively during the last 50 years. In contrast, the transient behavior of these systems remains practically unexplored. Transient characteristics, however, may have significant manufacturing implications. Indeed, if, for example, transients are sluggish and the steady state is reached only after a relatively long settling time, the production system may lose some of its throughput, thus leading to a lower efficiency. This paper is devoted to analytical and numerical investigation of the transient behavior of serial production lines with machines having the Bernoulli reliability model. The transients of the states (i.e., the probabilities of buffer occupancy) are described by the Second Largest Eigenvalue (SLE) of the transition matrix of the associated Markov chain. The transients of the outputs (i.e., production rate, PR, and work-in-process, WIP) are characterized by both the SLE and Pre-Exponential Factors (PEF). We study SLE and PEF as functions of machine efficiency, buffer capacity and the number of machines in the system. In addition, we analyze the settling times of PR and WIP and show that the former is often much shorter than the latter. Finally, we investigate production losses due to transients and show that they may be significant in serial lines with relatively large buffers and many machines. To avoid these losses, it is suggested that all buffers initially be half full. For two- and three-machine lines these analyzes are carried out analytically; longer lines are investigated by simulations.

1 May 2013 in IIE Transactions
Verified
Journal Article
Closed access
LZLiang Zhang
Liang Zhang
CWChuanfeng Wang
Chuanfeng Wang
JAJorge Arinez
Jorge Arinez
SBStephan Biller
Stephan Biller
Transient behavior of production systems has significant practical and theoretical implications. However, analytical methods for analysis and control of production systems during transients remain largely unexplored. In the framework of serial production lines with Bernoulli machines and finite buffers, this article develops a mathematical model for transient analysis and derives closed-form expressions for evaluating the production rate, consumption rate, work-in-process, and probabilities of machine starvation and blockage during transients. In addition, a computationally efficient procedure based on recursive aggregation is developed to approximate the transient performance measures with high accuracy. Finally, based on the mathematical model derived, system-theoretic properties of several important system transient characteristics are studied.

1 February 2016 in International Journal of Production Research
Verified
Journal Article
Closed access
ZJZhiyang Jia
Zhiyang Jia
LZLiang Zhang
Liang Zhang
JAJorge Arinez
Jorge Arinez
GXGuoxian Xiao
Guoxian Xiao
In recent years, achieving high energy efficiency has become one of the primary goals in manufacturing, along with maintaining high productivity and quality. In many manufacturing systems, it is sometimes possible to temporarily switch off a machine to reserve energy, and switch it back on when a certain condition is met. Indeed, production control-based shop floor continuous improvement is recognised as one of the most cost-effective ways to achieve energy-efficient production. In this paper, we study serial production lines with Bernoulli machines and finite capacity buffers and assume that some of the machines in the line can be switched on and off during the production process according to a state-based feedback control policy. Mathematical models for the system under consideration are derived and analytical methods are developed for calculating the system performance measures during transients. Specifically, exact Markovian analysis is used for two- and three-machine lines in which the switch-on/off operations of only one machine is considered. For longer lines, the switch-on/off operations of multiple machines are considered and an aggregation-based approximation approach is applied to evaluate the system performance measures. Numerical experiments show that the method developed can be used to efficiently calculate the system’s performance with high accuracy.