Optimization and control of a stand-alone hybrid solid oxide fuel cells/gas turbine system coupled with dry reforming of methane

This paper presents the hybrid solid oxide fuel cells (SOFC)/gas turbine (GT) system coupled with dry reforming of methane (DRM). The DRM is a syngas producer by consuming greenhouse gas. The stand-alone (off-the-grid) power system is developed by using a combination of a post-burner, recuperators and pressurized recycles in place of external energy supplies. To address the stand-alone operation and meet the complete combustion condition for the burner, the optimal operating conditions are initially determined by solving a constrained optimization algorithm for maximizing the hybrid power efficiency, and the dynamic control loops are implemented in a plantwide environment. In the proposed plantwide control strategy, the inventory control framework is added to regulate the plant component inventory, an air/fuel cross-limiting combustion control is added to ensure complete combustion and reduce heat loss, and the power and CO₂ emission control configuration is added to achieve the quality control performance. Finally, the simulation shows that the IMC-based multi-loop control scheme can efficiently regulate the total system power and control CO₂ emissions per kWh of electricity as well.     

需求不确定性对条件风险价值约束库存系统的影响

研究风险偏好和需求不确定性对库存系统的影响,证明最优订货量和最优利润关于缺货惩罚成本和风险水平的单调性。利用随机比较方法证明随机大需求导致较高的最优订货量,当不考虑缺货惩罚成本时随机大需求导致较高的最优利润;证明最优利润随需求可变性增加而减少,并给出相应的充分条件与充分必要条件;进一步证明存在一类需求分布,在一定条件下系统利润随需求可变性增加而增加。通过数值例子验证了所得研究结果。     

The EPQ model under conditions of two levels of trade credit and limited storage capacity in supply chain management

An inventory problem involves a lot of factors influencing inventory decisions. To understand it, the traditional economic production quantity (EPQ) model plays rather important role for inventory analysis. Although the traditional EPQ models are still widely used in industry, practitioners frequently question validities of assumptions of these models such that their use encounters challenges and difficulties. So, this article tries to present a new inventory model by considering two levels of trade credit, finite replenishment rate and limited storage capacity together to relax the basic assumptions of the traditional EPQ model to improve the environment of the use of it. Keeping in mind cost-minimisation strategy, four easy-to-use theorems are developed to characterise the optimal solution. Finally, the sensitivity analyses are executed to investigate the effects of the various parameters on ordering policies and the annual total relevant costs of the inventory system.     

Economic production quantity with rework process at a single-stage manufacturing system with planned backorders

In traditional inventory models such as the economic order quantity (EOQ) and the economic production quantity (EPQ) the sole objective is to minimize the total inventory-related costs, typically holding cost and ordering cost. These models do not consider the presence of defective products in the lot or rework of them. Recently, Jamal, Sarker, and Mondal (Jamal, A. A. M., Sarker, B. R., & Mondal, S., (2004). Optimal manufacturing batch size with rework process at single-stage production system. Computers and Industrial Engineering, 47(1), 77–89) proposed a model, which dealt with the optimum batch quantity in a single-stage system in which rework is done by addressing two different operational policies to minimize the total system cost, but their models do not consider planned backorders. In this direction, this paper develops an EPQ type inventory model with planned backorders for determining the economic production quantity for a single product, which is manufactured in a single-stage manufacturing system that generates imperfect quality products, and all these defective products are reworked in the same cycle. We also establish the range of real values of the proportion of defective products for which there is an optimal solution, and the close form for the total cost of inventory system. The use of the inventory model is illustrated with numerical examples. The classical EOQ, EPQ inventory models with or without planned backorders and Jamal, Sarker and Mondal’s model (Jamal, A. A. M., Sarker, B. R., & Mondal, S., (2004). Optimal manufacturing batch size with rework process at single-stage production system. Computers and Industrial Engineering, 47(1), 77–89) are shown to be special cases of the EPQ inventory model presented in this paper.     

Joint quality control and preventive maintenance strategy for imperfect production processes

In this paper, we develop a joint quality control and preventive maintenance policy for a production system producing conforming and nonconforming units. The considered system consists of one machine which must supply another production line operating on a just-in-time basis. Each lot produced by the machine is subject to a quality control. According to the proportion l of nonconforming units observed and compared to a threshold value l _m , one decides to undertake or not maintenance actions on the system. In order to palliate perturbations caused by the stopping of the machine for preventive and corrective maintenance actions of random durations, a buffer stock h is built up to ensure the continuous supply of the subsequent production line. The proposed strategy is modelled using simulation and experimental design. This approach allows to generate a second order response surface allowing to easily determine the optimal rate, l_m^*{l_{m}^*}, of nonconforming units on the basis of which preventive maintenance actions should be performed, and the optimal size, h*, of the buffer stock to be built. These values minimize the total cost per time unit which includes the costs related to maintenance, quality and inventory.     

(n,N) type maintenance policy for multi-component systems with failure interactions

This paper studies maintenance policies for multi-component systems in which failure interactions and opportunistic maintenance (OM) involve. This maintenance problem can be formulated as a Markov decision process (MDP). However, since an action set and state space in MDP exponentially expand as the number of components increase, traditional approaches are computationally intractable. To deal with curse of dimensionality, we decompose such a multi-component system into mutually influential single-component systems. Each single-component system is formulated as an MDP with the objective of minimising its long-run average maintenance cost. Under some reasonable assumptions, we prove the existence of the optimal (n, N) type policy for a single-component system. An algorithm to obtain the optimal (n, N) type policy is also proposed. Based on the proposed algorithm, we develop an iterative approximation algorithm to obtain an acceptable maintenance policy for a multi-component system. Numerical examples find that failure interactions and OM pose significant effects on a maintenance policy.     

A new order splitting model with stochastic lead times for deterioration items

In unreliable supply environments, the strategy of pooling lead time risks by splitting replenishment orders among multiple suppliers simultaneously is an attractive sourcing policy that has captured the attention of academic researchers and corporate managers alike. While various assumptions are considered in the models developed, researchers tend to overlook an important inventory category in order splitting models: deteriorating items. In this paper, we study an order splitting policy for a retailer that sells a deteriorating product. The inventory system is modelled as a continuous review system (s, Q) under stochastic lead time. Demand rate per unit time is assumed to be constant over an infinite planning horizon and shortages are backordered completely. We develop two inventory models. In the first model, it is assumed that all the requirements are supplied by only one source, whereas in the second, two suppliers are available. We use sensitivity analysis to determine the situations in which each sourcing policy is the most economic. We then study a real case from the European pharmaceutical industry to demonstrate the applicability and effectiveness of the proposed models. Finally, more promising directions are suggested for future research.     

Optimal maintenance policy for multi-component systems under Markovian environment changes

In this paper, we study multi-component systems, which environmental conditions and opportunistic maintenance (OM) involve. Environmental conditions will exert an influence on deterioration processes of the components in the system. For each component, the worse the environmental conditions are, the faster its deterioration speed is. We want to determine when to preventively maintain each component under such environmental influence. Our purpose is to minimize its long-run average maintenance cost. We decompose such a multi-component system into mutually influential single-component systems, and formulate the maintenance problem of each component as a Markov decision process (MDP). Under some reasonable assumptions, we prove the existence of the optimal (n_r, N_r) type policy for each component. A policy iteration method is used to calculate its optimal maintenance policy. Based on the method, we develop an iterative approximation algorithm to obtain an acceptable maintenance policy for a multi-component system. Numerical examples find that environmental conditions and OM pose significant effects on a maintenance policy.     

Comparisons of some improving strategies on MOPSO for multi-objective (r, Q) inventory system

This paper presents comparisons of some recent improving strategies on multi-objective particle swarm optimization (MOPSO) algorithm which is based on Pareto dominance for handling multiple objective in continuous review stochastic inventory control system. The complexity of considering conflict objectives such as cost minimization and service level maximization in the real-world inventory control problem needs to employ more exact optimizers generating more diverse and better non-dominated solutions of a reorder point and order size system. At first, we apply the original MOPSO employed for the multi-objective inventory control problem. Then we incorporate the mutation operator to maintain diversity in the swarm and explore all the search space into the MOPSO. Next we change the leader selection strategy used that called geographically-based system (Grids) and instead of that, crowding distance factor is also applied to select the global optimal particle as a leader. Also we use ε-dominance concept to bound archive size and maintain more diversity and convergence in the MOPSO for optimizing the inventory control problem. Finally, the MOPSO algorithms created using these strategies are evaluated and compared with each other in terms of some performance metrics taken from the literature. The results indicate that these strategies have significant influences on computational time, convergence, and diversity of generated Pareto optimal solutions.     

A geometric process model for M/PH(M/PH)/1/K queue with new service machine procurement lead time

In this article, we consider a geometric process model for M/PH(M/PH)/1/K queue with new service machine procurement lead time. A maintenance policy (N???1,?N) based on the number of failures of the service machine is introduced into the system. Assuming that a failed service machine after repair will not be ‘as good as new’, and the spare service machine for replacement is only available by an order. More specifically, we suppose that the procurement lead time for delivering the spare service machine follows a phase-type (PH) distribution. Under such assumptions, we apply the matrix-analytic method to develop the steady state probabilities of the system, and then we obtain some system performance measures. Finally, employing an important Lemma, the explicit expression of the long-run average cost rate for the service machine is derived, and the direct search method is also implemented to determine the optimal value of N for minimising the average cost rate.     

Robust Optimal Disturbance Observer Design for the Non‐Minimum Phase System

In this paper, a design strategy of robust disturbance observer is proposed systematically for stable non‐minimum phase systems. This strategy synthesizes the internal and robust stability, relative order and mixed sensitivity design requirements together to establish the optimization function. The optimal solution is obtained by standard H_∞ control theory under the condition of guarantying the presented requirements. Simulation results of a rotary mechanical system show the effectiveness of the proposed strategy.     

Modelling material flow using the Milk run and Kanban systems in the automotive industry

Material flow management refers to the analysis and specific optimization of the inventory‐production system. Material flow can be characterized as the organized flow of material in a production process with the required sequence determined by a technological procedure. The Milk run system assures the transportation of materials at the right time and in an optimal manner. It should be combined with the Kanban system to highlight when something is required in the production process. This paper presents biological swarm intelligence, in general, and a particular model, particle swarm optimization (PSO), for modelling material flow using a Milk run system supported by a Kanban system in the automotive industry. The aim of this study is to create a new model for the optimal number of trailers for one train and optimal number of containers in a tugger train system when the route time period has been defined. A new modified PSO approach for integrating inventory‐production in a unique optimization model is used. The major modification to the original PSO is using the capacity of a container instead of a velocity component. Each new Kanban trigger is checked, and the total timing for the Milk run delivery solution is calculated for the necessary raw material capacity for each shop floor.     

H 2 design of one-degree-of-freedom decoupling controllers for square plants

Decoupling design of one-degree-of-freedom controllers is treated for the generalised plant model within the H ₂ framework. The class of all realisable closed loop transfer matrices is parametrised under a mild assumption on non-unity feedback sensors. A set of compact assumptions is presented to guarantee the existence of the optimal H ₂ controller. Together with the optimal one, the class of all H ₂ controllers that yield finite H ₂ cost is obtained. The optimal closed transfer matrix and its associated controller are shown to be strictly proper under the reasonable order assumptions on the generalised plant.     

基于订货阈值的供应商延期支付策略设计

针对完全信息下以供应商为核心企业的二级供应链库存系统,将全单位延期支付与部分延期支付两种手段相结合,并在考虑延期支付期限与订货量相关的条件下,设计了基于供应商视角和订货阈值的延期支付策略,从而得出此策略能使系统利润达到帕累托最优.最后,通过数值算例对相关结论进行了验证和灵敏度分析.     

A Semi-Markov Inventory Control Model

Controlled semi-Markov processes for the analysis of a multi-product model of inventory control theory are considered. For this model, under decreasing functions of general costs, the existence conditions for the optimal strategy are found and the existence of optimal (,) s S –strategy in inventory control is proved.     

Optimization of growth of peptide chain by ribosomes on messenger RNA

To elucidate the integrated functional properties and organization strategy of the peptide elongation process of ribosomes on messenger RNA, we took a theoretical approach by applying a linear system analysis and optimal hypothesis. The basic theoretical model published by Gerst in 1965 was founded on reported experimental data. We have simplified the mechanism of the peptide elongation process by making the following assumptions. (1) When the left-most site (the 5′ terminal) on the messenger RNA is empty, the newly arrived amino-acyl-transfer-RNA (AT) links to the 5′ terminal even though other sites are empty. (2) When all other sites on the ribosomes except the 5′ terminal are empty and the first ribosome is not yet filled, ATs which arrive subsequently continue to bind to the 5′ terminal site of the first ribosome until the first ribosome has been filled. (3) When a given ribosome has been filled by an amount of product equivalent to the product ofp (amino acid residues) andq ribosomes, the filled ribosome advances to the next ribosomal region (q+1). There, the amino acid attainspq+1. After this transition, theqth ribosomal region becomes empty. (4) When the sites on the ribosomes are not all filled, newly arrived AT binds from the right of the total sequence. By applying the mass action law, the elongation process was expressed by 23 rate equations. The rate constants for the binding ribosome, turn over, peptide bond formation and transitional movement of ribosomes were utilized from reported experimental data. The optimal state was defined when the square of the concentration of all the transitional states and control input were minimized. This means that the elongation process is in the most economical state when there are no excessive changes at any steps of the elongation process and the least energy consumption. Linear system analysis showed that system was stable and controllable. The singular value was depressed by system optimization. The impulse response terminated earlier by a smaller peak amplitude in the optimized system than in those without optimization. The present model under optimal control is available to evaluate the functions of peptide synthesis on a messenger RNA, and to produce artificial protein from the standpoint of system optimization.     

A real-time inventory decision system using Western Electric run rules and ARMA control chart

Inventory management is an important area of production control. In 1999, Pfohl et al. [Pfohl, H.-C., Cullmann, O., & Stölzle, W. (1999). Inventory management with statistical process control: Simulation and evaluation. Journal of Business Logistics, 20, 101–120] developed a real-time inventory decision support system by using the individual control charts for monitoring the inventory level (i.e., stock quantity) and the market demand, in which a series of decision rules are provided to help the inventory manager to determine the time and the quantity to order. In the present paper, a real-time inventory decision system is proposed by incorporating Western Electric run rules into the decision rules of the system. Since the data of demand sometimes present a pattern of time series (i.e., autocorrelation may exist in the data of demand), in the proposed decision system the ARMA control chart is employed to monitor the market demand and the individual control chart is used to monitor the inventory level. A simulation study is conducted to investigate the effects of demand pattern and autocorrelation on the proposed inventory decision system and to verify the effectiveness of the system. The index “service level” is selected as the key indicator for the system performance. Based on the results of the simulation study, it is shown that the performance of the proposed inventory decision system is quite consistent with service level always greater than 90% for various demand patterns.     

Simultaneous determination of the optimal production–inventory and product inspection policies for a deteriorating production system

In this paper, we attempt to find a method for the optimization of production–inventory and product inspection policies for deteriorating production systems. Taking advantage of the nature of a deteriorating production system, a strategy would be not to inspect the first s items of the batch. Therefore, an inspection policy which disregards the first s (DTF-s) items of the batch is proposed. Under the DTF-s policy, we do not inspect the first s produced items but inspect only those items from the (s+1)th till the end of the production run. The objective of this study was the joint determination of the production lot size and the inspection policy s, resulting in a minimization of the expected average cost per unit time. Based on this model, the underlying conditions necessary for the existence of an optimal policy are given. Two commonly used inspection strategies, no inspection and full inspection are discussed. Under both inspection strategies, an optimal production–inventory lot is bounded by the traditional economic quantity. The case of full inspection is shown to be an extension of previously reported results. The option of investing in the process of quality improvement is also discussed. Finally, numerical examples are given to illustrate the method and its advantages in the conclusion.Scope and purposeThis paper considers the relationship between production, inventory and inspection in a deteriorating production system which may transit from the “in-control” state to the “out-of-control” state after a period of operation. Once the transition to the “out-of-control” state has occurred, it is assumed that some percentage of the items produced are defective or of substandard quality. However, in many cases, defects in a defective item can only be identified by an inspection process which carries an inspection cost. Those inspected items which are found to be defective are reworked at some cost before being shipped. On the other hand, defective items which are not inspected will be passed to the customer, incurring a much larger warranty cost. In order to operate such a system economically, tradeoffs among production setup, inventory, inspection and defective cost must be analyzed. Deterioration of the production system is an inherent process in all manufacturing industries. An understanding of the relationship among production, inventory and inspection for such systems will help managers to maintain efficient and economic control of operations.     

Optimal Strategies for Inventory Control Systems with a Convex Cost Function

Some controlled Markovian processes in discrete time in the context of optimization of inventory control systems are studied. Optimality of (s, S)-policies for the case of convex cost functions is proved using theorems on existence and uniqueness of a nonrandomized stationary optimal policy for Markovian processes with discrete time and a continuous control set for criteria characterizing mean costs per unit time and overestimated total costs and Bellman equations.     

Containment strategies of epidemic invasions

In this paper, prompted by the practical issue of controlling the Aujeszky disease affecting hogs, we analyse what strategies can be implemented to try and contain an SI epidemic invasion in one and two neighbouring farms. We perform some simulations under different assumptions on the basic system, leading thus to different models. The results show that the disease cannot be arrested completely, since infected remain so for life and the system is of a diffusive type, but its spread can rather be slowed down. The influence of contamination islands, sudden external disease infiltration and containment barriers are simulated. The possible leaking of the infection into a neighbouring farm is also studied. The analysis is then extended to an SIS model allowing disease recovery. Under suitable conditions, harvesting is shown to be an effective containment strategy.