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This paper studies demand satisfaction and decision-making for a printed circuit board (PCB) manufacturing system. A performance indicator, the system reliability, is proposed to evaluate the demand satisfaction. In particular, two important characteristics, (i) multiple production lines in parallel and (ii) multiple repair actions, are considered in this study. The PCB manufacturing system is modelled as a stochastic-flow manufacturing network (SFMN) by the graphical transformation and decomposition techniques. Based on the network-structured SFMN, this paper develops an algorithm to generate all minimal capacity vectors that workstations should provide to satisfy a given demand. In terms of all minimal capacity vectors, the system reliability is derived. In addition, the reliable production policy is determined based on each single minimal capacity vector. [ABSTRACT FROM AUTHOR]

This paper presents a fuzzy-based assessment model to evaluate system reliability of a labour-intensive manufacturing system with repair actions. Due to the uncertainty in human performance, labour-intensive manufacturing systems must determine the capacity of each labourer in order to accurately characterise the performance of the systems. Therefore, we model such a manufacturing system as a fuzzy multi-state network in order to characterise the labourers’ influence on workstation performance. First, the workstation reliability is defined according to the loading state by three fuzzy membership functions, namely ‘under loading’, ‘normal loading’ and ‘over loading’, respectively. The system reliability is subsequently evaluated with fuzzy intersection operations in terms of these workstation reliabilities. Thus, the system reliability is defined as a fuzzy membership function to assess whether the manufacturing system performance is sufficient to satisfy the demand reliably. A case study of a footwear manufacturing system is illustrated to explain the proposed model. Furthermore, we apply the proposed model to a non-labour-intensive manufacturing network in order to validate the applicability to this class of systems. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

This paper develops a three-phase procedure to measure the performance of a highly value-added footwear manufacturing system taking reworking actions into account, in which the system consists of multiple production lines. We mainly address the system reliability as a performance indicator to evaluate the possibility of demand satisfaction. First, we construct the manufacturing system as a manufacturing network by graphical transformation and decomposition. Second, capability analysis is implemented to determine the input flow of each station based on the manufacturing network. Third, a simple algorithm is proposed to generate all minimal capacity vectors that stations should provide to satisfy the given demand. We evaluate the system reliability in terms of the minimal capacity vectors. A further decision making issue is discussed to decide a reliable production strategy. Whenever the system state changes, the proposed performance evaluation procedure can be implemented easily and flexibly. [ABSTRACT FROM PUBLISHER]

From the perspective of network analysis, the manufacturing system can be constructed as a stochastic-flow network, since the capacity of each machine is stochastic (i.e. multistate) owing to the failure, partial failure, and maintenance. Considering reworking action and different failure rates of machines, the input flow (raw materials/work in process) processed by each machine might be defective, and therefore the output flow (work in process/products) would be less than the input amount. To evaluate the capability of the manufacturing system, we measure the probability that the manufacturing network can satisfy demand. Such a probability is defined as the system reliability. A decomposition method is first proposed to divide the manufacturing network into one general processing path and one reworking path. Subsequently, two algorithms are utilised for different network models to generate the lower boundary vector of machine capacity to guarantee that the manufacturing network is able to produce sufficient products fulfilling the demand. The system reliability of the manufacturing network can be derived in terms of such a capacity vector afterwards. [ABSTRACT FROM PUBLISHER]

In a project, duration and cost of activities are stochastic in nature due to uncertainties (natural disaster and human factors). Thus, a project is commonly modeled as a stochastic project network (SPN). For a project manager, it is a duty to manage both efficiency and effectiveness of an SPN. To achieve this goal, this paper develops a procedure to derive project reliability interval for an SPN. The project reliability interval is a performance indicator to assess the probability of project completion under budget and time constraints. Such an indicator provides project manager a quantitative measurement and a qualitative implication to decide a reasonable completion time and budget for an SPN. Quantitative measurement shows the efficiency of budget and time consumption to complete a project; while qualitative implication provides the effectiveness after implementing a project. A practical project of disaster recovery system is utilized to demonstrate how the project reliability interval is applicable in the real life. Sensitivity analysis is further implemented to investigate the project reliability interval under various constraints of project time and budget. [ABSTRACT FROM AUTHOR]

Network reliability is an important performance index for many real-life systems, such as electric power systems, computer systems and transportation systems. These systems can be modelled as stochastic-flow networks (SFNs) composed of arcs and nodes. Most system supervisors respect the network reliability maximization by finding the optimal multi-state resource assignment, which is one resource to each arc. However, a disaster may cause correlated failures for the assigned resources, affecting the network reliability. This article focuses on determining the optimal resource assignment with maximal network reliability for SFNs. To solve the problem, this study proposes a hybrid algorithm integrating the genetic algorithm and tabu search to determine the optimal assignment, called the hybrid GA-TS algorithm (HGTA), and integrates minimal paths, recursive sum of disjoint products and the correlated binomial distribution to calculate network reliability. Several practical numerical experiments are adopted to demonstrate that HGTA has better computational quality than several popular soft computing algorithms. [ABSTRACT FROM AUTHOR]

To maintain a competitive edge, technology manufacturers must produce systems that are reliable enough to satisfy customers yet cheap enough to engineer so that they are profitable. This paper presents an optimization model to maximize the statistical confidence in product profitability, permitting flexibility in the design and number of the units manufactured. This is unlike traditional approaches, which focus on the two cases that optimize the reliability of a single unit or the s -expected profit obtained from a very large number of units. These two extremes disregard a practical concern, namely the negative impact that a larger than s -expected number of failures will exert on product profitability. This paper formulates an optimization problem to mitigate this risk. Virtually all reliability optimization problems also assume that component failures are s -independent. The present paper does not impose this assumption. The utility of the approach is demonstrated through a series of examples which compare the reliability of systems designed with and without the assumption of s -correlated component failures. The results indicate that explicitly considering s -correlation consistently mitigates the risk to profitability more effectively than the same method when component failures are assumed to be s -independent. [ABSTRACT FROM AUTHOR]

Background: This study examined the association between methylenetetrahydrofolate reductase ( MTHFR) polymorphisms and survival of patients with colorectal cancer (CRC) treated with 5-fluorouracil (5-FU)-based chemotherapy in Taiwan. Methods: We genotyped MTHFR polymorphisms C677T (rs1801133) and A1298C (rs1801131) for 498 CRC patients treated with 5-FU-based chemotherapy after receiving surgery. Survival analyses on MTHFR polymorphisms were performed using log-rank test and Kaplan-Meier curve. Cox proportional hazards models were used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between MTHFR genotypes and survival. Results: Overall survival (OS) was significantly longer in CRC patients with MTHFR 677 CT+TT genotypes compared with those with 677 CC genotype (HR 0.77; 95% CI 0.60-0.98). Although the MTHFR A1298C polymorphism was not associated with OS in CRC, this polymorphism was associated with significantly shorter OS in rectal cancer. Among rectal cancer patients, OS was shorter for patients with AC+CC genotypes than for those with the AA genotype (HR 1.95; 95% CI 1.35-2.83). In haplotype analysis, better OS was found for colon cancer patients carrying the MTHFR 677T-1298A haplotype (HR 0.73; 95% CI 0.55-0.97), but worse survival was linked to rectal cancer patients carrying the MTHFR 677C-1298C haplotype (HR 1.53; 95% CI 1.08-2.18). Conclusions: Our findings suggest that MTHFR genotypes provide prognostic information for CRC patients treated with 5-FU-based chemotherapy. [ABSTRACT FROM AUTHOR]

This article presents a topological technique for evaluating the performance of a hybrid flow-shop production system. Such a production system is modeled as a hybrid production network; each workstation of the hybrid production network has stochastic capacity levels. This article evaluates the probability of demand satisfaction as a performance indicator for the hybrid production network, in which the network has multiple lines and each workstation has a distinct defect rate. First, a topological transformation is utilized to transform a hybrid flow-shop production system into a network-structured hybrid production network; then, the hybrid production network is decomposed into several routes for flow analysis. Second, two procedures for two models (Model I considers the hybrid production network with parallel lines, Model II with intersectional lines) are designed to generate the minimal required capacity for workstations to satisfy the given demand. The probability of demand satisfaction is subsequently evaluated in terms of the minimal required capacities by applying the recursive sum of disjoint products algorithm. [ABSTRACT FROM AUTHOR]

This study develops a multistate freight network for single and perishable merchandise to assess the freight performance, where a node denotes a supplier, a distribution centre, or a buyer, while a logistics company providing a freight traffic service is denoted by an edge. For each logistics company, carrying capacity should be multistate since partial capacity may be reserved by some customers. The merchandise may perish or be perished during conveyance because of disadvantageous weather or collision in carrying such that the number of intact cargoes may be insufficient for the buyers. Hence, according to the perspective of supply chain management, the reliability, a probability of the network to successfully deliver the cargoes from the suppliers to the buyers subject to a budget, is proposed to be a performance index, where the suppliers and buyers are not the previous customers. An algorithm in terms of minimal paths to assess the reliability is developed. A fruit logistics case is adopted to explore the managerial implications of the reliability using sensitivity analysis. [ABSTRACT FROM AUTHOR]

In recent years, the system maintenance service has been transitioning from the resource-based contract (RBC) approach towards a new outcome-based contract (OBC) approach, enabling better profits for the service provider and lower cost and risk equilibrium for the service buyer. Prior studies usually focus on a single criterion as a service outcome for a complex and repairable system. This paper proposes a novel risk equilibrium OBC model with a given multi-outcome in maintenance service. The proposed model solves the multi-criteria obligation problem in a complex repairable system maintenance service to achieve three objectives: searching for a dominant risk equilibrium and inner cost, attaining the system's expected outcome, and controlling the multi-outcome and risk equilibrium. The proposed model can apply to disparate maintenance policies comprising various preventive and corrective maintenance methods. Furthermore, the proposed model presents a comparative mechanism to different contract types by game-theoretical analysis, which leads to a first-best solution and avoids moral hazard problems. The case study shows that the proposed OBC model forms a game-theoretical equilibrium for both parties, ensuring the risk equilibrium with the optimal cost. [ABSTRACT FROM AUTHOR]