Cheng-Fu Huang

Network reliability with deteriorating product and production capacity through a multi-state delivery network

Delivery process is a critical issue from the viewpoint of supply chain management. However, in the delivery process, deterioration would occur because of natural disasters (e.g. earthquake, fire, flood, hurricane and landslide) or man-made factors (e.g. explosion, terrorist attack and vehicular collision). The results in the intact products arriving at the market may not satisfy the demand. This paper thus concentrates on a multi-state delivery network (MSDN) with multiple suppliers, in which a vertex denotes a supplier, a transfer station or a market, while a branch denotes a carrier providing the delivery service for a pair of vertices. The available capacity of the carrier responsible for the delivery on a branch is multi-state because the capacity may be partially reserved by other customers. The addressed problem is to evaluate the network reliability, the probability that the MSDN with the deterioration consideration can satisfy the market demand within the budget and production capacity limitations. An algorithm is developed in terms of minimal paths to evaluate the network reliability along with a numerical example to illustrate the solution procedure. A real case study of the deteriorating auto glass is utilised to demonstrate the utility of the proposed algorithm.

Reliability evaluation of a stochastic-flow distribution network with delivery spoilage

From the supply chain management perspective, this paper focuses on evaluating network reliability of a stochastic-flow distribution network (SFDN) under the delivery spoilage consideration. An SFDN is composed of nodes and routes, where each node denotes a supplier, a transfer center, or a market, and each route connects a pair of nodes. Along each route, there is a carrier whose available capacity is stochastic. Moreover, goods may rot or be spoilt during delivery due to traffic accidents, collisions, natural disasters, weather, time, etc., and thus the intact goods may not satisfy the market demand. Network reliability is defined as the probability that the SFDN can satisfy the market demand under the delivery spoilage consideration and the delivery budget constraint, and can be regarded as a performance index for distribution activity in supply chain management. An algorithm is developed in terms of minimal paths to evaluate network reliability. A numerical example is given to illustrate the solution procedure. Then a practical case of fruit distribution is presented to emphasize the management implication of network reliability.

System reliability evaluation of a touch panel manufacturing system with defect rate and reworking

In recent years, portable consumer electronic products, such as cell phone, GPS, digital camera, tablet PC, and notebook are using touch panel as interface. With the demand of touch panel increases, performance assessment is essential for touch panel production. This paper develops a method to evaluate system reliability of a touch panel manufacturing system (TPMS) with defect rate of each workstation and takes reworking actions into account. The system reliability which evaluates the possibility of demand satisfaction can provide to managers with an understanding of the system capability and can indicate possible improvements. First, we construct a capacitated manufacturing network (CMN) for a TPMS. Second, a decomposition technique is developed to determine the input flow of each workstation based on the CMN. Finally, we generate the minimal capacity vectors that should be provided to satisfy the demand. The system reliability is subsequently evaluated in terms of the minimal capacity vectors. A further decision making issue is discussed to decide a reliable production strategy.

Stochastic computer network under accuracy rate constraint from QoS viewpoint

In the past, the main concerns for competitive enterprise environment of computer networks were data transmission delays and costs. However, from the viewpoint of quality of service (QoS), internet service providers and enterprise customers are increasingly focusing on data accuracy during transmission. This study extends a stochastic computer network (SCN) to evaluate the system reliability, where the system reliability is the probability that demand can be transmitted through the SCN under the total accuracy rate. In such an SCN, each arc has several capacities, and an accuracy rate. We can regard the system reliability as a measurable index for assessing the SCN performance. A lower boundary point for (d,K) is a minimal capacity vector, which allows the system to transmit demand d under the total accuracy rate K. Using the minimal paths, we propose an efficient algorithm to find all lower boundary points for (d,K). The system reliability can then be computed in terms of all lower boundary points for (d,K) by the recursive sum of disjoint products (RSDP) algorithm. Several numerical examples are demonstrated to illustrate the utility, efficiency, and effectiveness of the proposed algorithm.

A reliability indicator to measure a stochastic supply chain network with transportation damage and limited production capacity

This article proposes a reliability measurement for a supply chain network, in which a vertex denotes a supplier, a transfer center, or a customer, while a route connecting a pair of vertices denotes a carrier. Each carriers available transportation capacity (e.g., number of containers) is not deterministic since the transportation capacity may be partially reserved by other customers. Thus, the supply chain network can be regarded as a Stochastic Supply Chain Network (SSCN). In an SSCN with multiple suppliers and markets, the goods may be damaged due to traffic accident, natural disaster, inclement weather, time, or collision during transportation such that the intact goods may not meet the customers demands. In addition, the goods supplied by a specified supplier cannot exceed its production capacity, and the total transportation cost cannot exceed a budget. SSCN reliability is defined as the probability that the SSCN can successfully deliver goods to multiple customers subject to a specified level of damage, budget, and limited production capacity. An algorithm is proposed to evaluate the SSCN reliability based on minimal paths. A real case study of a pineapple supply chain network is utilized to demonstrate the utility of the proposed algorithm.

Backup reliability assessment within tolerable packet error rate for a multi-state unreliable vertex computer network

Abstract From the viewpoint of quality of service, the packet error rate (PER) and delivery time are both of critical performance indicators to assess internet quality for supervisor and customers. A computer network is composed of Internet data centers and delivery mediums and we can regard it as a network topology with vertices and arcs. Virtually, each component (vertex or arc) has multiple capacities/states due to failure, maintenance, etc. Evaluating the reliability of a network with unreliable vertices is a difficult problem because of the disabled of adjacent arcs by vertex failure. Hence the network with unreliable vertices can be called a multi-state unreliable vertex computer network (MUVCN). Concentrating on the MUVCN, this paper addresses the data delivery from the source to the sink through k ( k ⩾ 2 ) disjoint minimal paths simultaneously, and proposes an algorithm to assess system reliability fulfilling demand constraint, tolerable PER, and time threshold. Furthermore, a routing strategy for raising system reliability is established in advance to specify the main and backup minimal paths. Subsequently, such a system reliability named the backup reliability can be computed faster.

Stochastic Flow Network Reliability with Tolerable Error Rate

Abstract Service-level agreements for data transmission often define criteria such as availability, delay, and loss. Internet service providers and enterprise customers are increasingly focusing on tolerable error rate during transmission. Focusing on a stochastic flow network (SFN), this study extends reliability evaluation to considering tolerable error rate, in which network reliability is the probability that demand can be satisfied. In such an SFN, each component (branch or node) has several capacities and a transmission error rate. Network reliability can be regarded as a performance index for assessing the SFN. We propose an efficient algorithm based on minimal paths to find all minimal capacity vectors that allow the network to transmit d units of data under tolerable error rate E. Network reliability is computed in terms of such vectors by the recursive sum of disjoint products algorithm. The proposed algorithm is tested for a benchmark network and the National Science Foundation Network. The computational complexity of the proposed algorithm is analyzed as well.

Estimated network reliability evaluation for a stochastic flexible flow shop network with different types of jobs

A flexible flow shop (FFS) with stochastic capacity is studied.A stochastic flexible flow shop (SFFSN) network is constructed to model the FFS.Propose an index, network reliability, to measure the SFFSN.A branch-and-bound approach is involved to evaluate estimated network reliability.Two real cases are utilized to demonstrate network reliability evaluation. In fields such as integrated circuit packaging, printed circuit boards (PCB), and textile fabrication, flexible flow shops (FFSs) are common manufacturing systems and have been studied by several researchers. Previous studies on FFSs assume that the capacity of each station is fixed. However, owing to factors such as maintenance, partial failures, the possibility of failures, and unexpected situations in manufacturing systems, the capacity, i.e., the number of normal machines in a station should have multiple levels and be regarded as a stochastic component. Hence, this study extends the deterministic capacity to the stochastic case for each station. An FFS with stochastic capacity is modeled as a stochastic flexible flow shop network (SFFSN) where each arc denotes a station with stochastic capacity and each node denotes a buffer. To illustrate the ability of a system in satisfying an order in the FFS, this study evaluates the network reliability, which is defined as the probability with which the SFFSN can complete an order within the time constraint. Because the completion time of an order cannot be computed directly, this study proposes an algorithm involving a branch-and-bound approach for the evaluation of the estimated network reliability based on two approximate capacity vectors. Three real cases, IC card, PCB and footwear manufacturing systems, and computational experiments are utilized to demonstrate the proposed algorithm and to discuss the performance of the algorithm, respectively. The experimental results show that the proposed algorithm can acquire the estimated network reliability close to the accurate network reliability.

A simple algorithm to evaluate supply-chain reliability for brittle commodity logistics under production and delivery constraints

This paper focuses on developing a network model to evaluate supply-chain reliability for the brittle commodity logistics, in which the network is composed of branches and vertices. A vertex denotes a supplier, a transfer center, or a customer and a branch connecting a pair of vertices denotes a carrier. In the brittle commodity logistics network, each supplier has limited production capacity and the production cost is counted in terms of the number of the provided goods. Moreover, the delivery capacity (e.g. number of containers) provided by any carrier is multistate because the partial capacities may be reserved for other customers, and the delivery cost is counted in terms of the consumed delivery capacity. In the brittle commodity delivery, the goods may be damaged by natural disasters, traffic accidents, collisions, and so on, such that the intact goods can not satisfy the customer demand. Hence the delivery damage should be considered while evaluating the performance of a logistics network. This paper proposes the supply-chain reliability, which is defined as the probability of the network to successfully deliver goods to the customer with the delivery damage, limited production capacity, and budget considerations, to be a performance index. In terms of minimal paths, an algorithm is developed to evaluate the supply-chain reliability. A practical case of flat glass logistics is employed to discuss the management implications of the supply-chain reliability.

Assessing reliability within error rate and time constraint for a stochastic node-imperfect computer network:

In order to maintain the stability of a computer network, the assessment of system reliability is an important issue for the supervisor. A computer network can be modeled as a network topology with edges and nodes, in which each edge denotes a transmission line such as coaxial cables or fiber cables, and each node denotes a transmission station such as router or switch. For a real-life computer network, the capacity of each component (edge or node) should be stochastic owing to complete failure, partial failure, etc. Hence, the computer network with imperfect components is also stochastic and is named a stochastic node-imperfect computer network. Different from the quickest path problem considering deterministic capacity, this article concentrates on a stochastic node-imperfect computer network to evaluate the probability that d units of data can be transmitted within tolerable error rate and time constraint. Such a probability, called system reliability, is a performance indicator to provide to managers for further improvement. An efficient algorithm in terms of the approach of minimal paths to evaluate the system reliability is proposed.