Abstract The profile monitoring is an important tool for quality control. Most of existing profile monitoring approaches focus on monitoring single profile. In practice, multiple profiles also widely exist and these profiles contain rich correlation information that can benefit the monitoring of interested/target profile. In the paper, we propose a transfer learning framework to extract profile-to-profile

Abstract Empirical models that relate multiple quality features to a set of design variables play a vital role in many industrial process optimization methods. Many of the current modeling methods usually employ a single-response normal model to analyze industrial processes without taking into consideration the high correlations and the non-normality among the response variables, and the problem of

Abstract Finite Element Analysis (FEA) has been widely used to generate simulations of complex nonlinear systems. Despite its strength and accuracy, FEA usually has two limitations: (i) running high-fidelity FEA often requires high computational cost and consumes a large amount of time; (ii) FEA is a deterministic method that is insufficient for uncertainty quantification when modeling complex systems

Abstract We introduce a new class of two-stage stochastic uncapacitated facility location problems under system nervousness considerations. The location and allocation decisions are made under uncertainty, while the allocation decisions may be altered in response to the realizations of the uncertain parameters. A practical concern is that the uncertainty-adaptive second-stage allocation decisions might

Abstract In this paper, an analytical method is introduced to evaluate the flow time of an assembly process with collaborative robots. In such a process, an operator and a collaborative robot can independently carry out preparation tasks first, then they work jointly to finish the assembly operations. To study the productivity performance of such systems, a stochastic process model is developed, where

Abstract In this paper, we address a two-stage scheduling problem which requires coordination between clinical and surgical appointments for specialized surgeries. First, patients have a clinical appointment with a surgeon to determine whether they are an appropriate candidate for the surgical procedure. Subsequently, if the decision to pursue the surgery is made the patient undergoes the procedure

Abstract The buffer allocation problem (BAP) in production flow lines is very relevant from a practical point of view and very challenging from a scientific perspective. For this reason, it has drawn great attention both in industry and in the academic community. However, despite the problem relevance, no exact method is available in the literature to solve it when long production lines have to be

Abstract Interaction event networks, which consist of interaction events among a set of individuals, exist in many areas from social, biological to financial applications. The individuals on networks interact with each other for several possible reasons, such as periodic contact or reply to former interactions. Regarding these interaction events as expectations based on previous interactions is crucial

Abstract The root-cause diagnostics of product quality defects in multistage manufacturing processes often requires a joint identification of crucial stages and process variables. To meet this requirement, this paper proposes a novel penalized matrix regression methodology for two-dimensional variable selection. The method regresses a scalar response variable against a matrix-based predictor using

Abstract This study is a response to the observation that little attention has been paid to the relationship between production (manufacturing) system design and product quality. In particular, only very limited work exists analyzing assembly system quality when multiple products are produced in the same system. Here, a computational scheme to estimate material, capacity and resource requirements in

Abstract Statistical process control (SPC) charts are widely used in the manufacturing industry for monitoring the performance of sequential production processes over time. A common practice in using a control chart is to first collect samples and take measurements of certain quality variables from them at equally-spaced sampling times, and then make decisions about the process status by the chart

ABSTRACT Markov decision processs (MDPs) have found success in many application areas that involve sequential decision making under uncertainty, including the evaluation and design of treatment and screening protocols for medical decision making. However, the data used to parameterize the model can influence what policies are recommended, and multiple competing data sources are common in many application

Abstract In the existing pH acceleration models, which are used to assess the shelf-life of liquid-type nano-sol products, a mixture of normal distributions is commonly employed for describing the sizes of particles mixing from two populations. The Gaussian mixture model approach falls short when used to characterize the asymmetric distributions of particle sizes in subgroups. This work considers instead

Editorial: Contributions to Sustainable Bioenergy Systems Design, Planning and Operations. IISE Transactions. Accepted 21 February 2021.

Abstract Overcrowding, long waiting times and delays frequently occur in hospital emergency departments (EDs). The main causes are the stochastic and strongly time-varying demands of patient arrivals at an ED and the temporary overloading of EDs. Motivated by collaboration with large EDs, we investigate the physicians scheduling problem in the ED for a weekly planning horizon to address the stochastic

Abstract Feature extraction for tensor data serves as an important step in many tasks such as anomaly detection, process monitoring, image classification, and quality control. Although many methods have been proposed for tensor feature extraction, there are still two challenges that need to be addressed: 1) how to reduce the computation cost for high dimensional and large volume tensor data; 2) how

Abstract The design and control of effective sortation systems have become more complex as both the volume of parcels and also the number of time-definite service options offered by parcel carriers have grown. In this paper, we describe approaches for planning two-stage parcel sort operations that explicitly consider time deadlines and sorting capacities. In two-stage sorting, parcels are sorted into

ABSTRACT In this paper, a multi-armed bandit problem is studied in an explore-then-commit setting where the cost of pulling an arm in the experimentation (exploration) phase may not be negligible. Identifying the best arm after a pure experimentation phase to exploit it once or for a given finite number of times is the goal of the problem. Applications of this are prevalent in personalized healthcare

Abstract The use of video-imaging data for in-line process monitoring applications has become popular in the industry. In this framework, spatio-temporal statistical process monitoring methods are needed to capture the relevant information content and signal possible out-of-control states. Video-imaging data are characterized by a spatio-temporal variability structure that depends on the underlying

ABSTRACT In this paper, a multi-armed bandit problem is studied in an explore-then-commit setting where the cost of pulling an arm in the experimentation (exploration) phase may not be negligible. Identifying the best arm after a pure experimentation phase to exploit it once or for a given finite number of times is the goal of the problem. Applications of this are prevalent in personalized healthcare

Abstract The use of video-imaging data for in-line process monitoring applications has become popular in the industry. In this framework, spatio-temporal statistical process monitoring methods are needed to capture the relevant information content and signal possible out-of-control states. Video-imaging data are characterized by a spatio-temporal variability structure that depends on the underlying

Abstract Data streams are prevalent in current manufacturing and service systems where real-time data arrive progressively. A quick distribution inference from such data streams at their early stages is extremely useful for prompt decision making in many industrial applications. For example, a quality monitoring scheme can be quickly started if the process data distribution is available and the optimal

Abstract While a large number of degradation models for industrial systems have been proposed by researchers over the past few decades, the modeling of impacts of maintenance actions has been mostly limited to single-component systems. Among multi-component models, past work either ignores the general impact of maintenance, or is limited to studying failure interactions. In this paper, we propose a

Abstract In reliability engineering, obtaining lifetime information for highly reliable products is a challenging problem. When a product quality characteristic whose degradation over time can be related to lifetime, then the degradation data can be used to estimate the first-passage (failure) time distribution and the mean-time-to-failure (MTTF) for a given threshold level. To model the degradation

Abstract We consider the problem of decision-making in Markov decision processes (MDPs) when the reward or transition probability parameters are not known with certainty. We consider an approach in which the decision maker (DM) considers multiple models of the parameters for an MDP and wishes to find a policy that optimizes an objective function that considers the performance with respect to each model

Abstract In this paper, we present a risk evaluation and maintenance strategy optimization approach for systems with parallel identical assets subject to continuous deterioration. System performance is defined by the number of functional assets, and the penalty cost is measured by the loss of performance. To overcome the practical challenges of information sparsity, we employ a Bayesian framework to

Abstract This paper presents a framework for profit-maximizing strategic bio-energy supply chain design by taking into account variability in biomass as a response to price set as well as uncertainty in biomass yield. We present our model as a two-stage stochastic integer program for a multi-period integrated design of a network in which the here-and-now strategic decisions include biorefinery locations

Abstract In this paper, we aim to solve Bayesian Risk Optimization (BRO), which is a recently proposed framework that formulates simulation optimization under input uncertainty. In order to efficiently solve the BRO problem, we derive nested stochastic gradient estimators and propose corresponding stochastic approximation algorithms. We show that our gradient estimators are asymptotically unbiased

Abstract The flowtime network restoration problem was introduced by Averbakh and Pereira (2012) who presented a Minimum Spanning Tree (MST) heuristic, two local search procedures, and an exact branch-and-bound (B&B) algorithm. This note corrects the computational results in Averbakh and Pereira (2012).

A cyber-additive manufacturing network (CAMNet) integrates connected additive manufacturing processes with advanced data analytics as computation services to support personalized product realization. However, highly personalized product designs (e.g., geometries) in CAMNet limit the sample size for each design, which may lead to unsatisfactory accuracy for computation services, e.g., a low prediction

Abstract Due to the recent advancements in the manufacturing system, the semiconductor FABs have become larger, and thus, more overhead hoist transports (OHTs) need to be operated. In this paper, we propose a cooperative zone-based rebalancing algorithm (CZR) to allocate idle overhead hoist vehicles (OHTs) in a semiconductor FAB. The proposed model is composed of two parts: (1) a state representation

Abstract The paper deals with cycle time calculation of Automated Storage and Retrieval Systems (AS/RS). Cycle time has a high impact on the operating performance of an AS/RS, and its knowledge is essential, both at the operational and design level. The novelty of the paper concerns the peculiar kind of system that is considered, as the focus is on the Shuttle-Lift-Crane AS/RS. This solution, common

Abstract In this paper we create a novel monitoring system to detect changes within a sequence of networks. Specifically, we consider sparse, weighted, directed, and attributed networks. Our approach uses the Hurdle model to capture sparsity and explain the weights of the edges as a function of the node and edge attributes. Here, the weight of an edge represents the number of interactions between two

Abstract This research examines a uniform-price auction mechanism in managing staffing for self-scheduling business such as task sourcing and work-from-home call centers. We consider two types of service providers: Type-1 agents who require advanced notice before a shift starts and Type-2 agents who are flexible enough to be scheduled on-demand. We develop an integrated framework that can jointly analyze

Abstract Chimeric antigen receptor T cell therapy has demonstrated innovative therapeutic effectiveness in fighting cancers; however, it is extremely expensive due to the intrinsic patient-to-patient variability in cell manufacturing. We propose in this work a novel calibration-free statistical framework to effectively deduce critical quality attributes under the patient-to-patient variability. Specifically

Abstract The traditional maritime logistics industry is facing an industry transformation bringing by technology development. Along with industry transformation, the maritime logistics research field is also facing new challenges and opportunities. It is found that using simulation or optimization alone to solve maritime logistics decision problems has some drawbacks. Instead, a trend of integrating

Abstract Most production environments are stochastic in nature due to the randomness inherent in the production processes. One important engineering problem commonly faced by practitioners is to determine optimal engineering tolerances to be used in production. This paper develops optimization models for determining tolerance sets to maximize the long-run average net profit on a production line with

Abstract This article addresses an underground mine design and scheduling problem, in which ore extraction methods are determined and resulting mining activities are scheduled. The mining method influences necessary infrastructure, the activities selected, and their timing. We divide the ore body into partitions (i.e., panels), each of which is extracted using a specific method, if at all. We consider

Abstract Many cities have to cope with annual snowfall, but are struggling to manage their snow plowing activities efficiently. Despite the fact that winter road maintenance has been a popular research subject for decades, very few papers propose scalable models that can incorporate side constraints encountered in real-life applications. In this work, we propose a Constraint Programming formulation

Abstract Accelerated destructive degradation tests (ADDTs) are effective for reliability assessment of highly reliable products whose key performance characteristic has to be destructively measured. Test units in a reliability experiment typically share the same test environments, and this introduces block effects to the resulting ADDT data. Nevertheless, the block effects are seldom considered in

Abstract As an effective dimension reduction and feature extraction technique, manifold learning has been successfully applied to high-dimensional data analysis. With the rapid development of sensor technology, a large amount of high dimensional data such as image streams can be easily available. Thus, a promising application of manifold learning is in the field of sensor signal analysis, particular

Abstract This article investigates spare parts service contracts for capital goods. We consider a single-item, single-location inventory system that serves one customer with multiple machines. During the contract execution phase, the true demand rate is observed. It can differ from the estimated demand rate because of two factors: increased demand variation in finite horizon settings and a shift in

Abstract The paired job scheduling problem seeks to schedule n jobs on a single machine, each job consisting of two tasks for which there is a mandatory minimum waiting time between the completion of the first task and the start of the second task. We provide complexity results for problems defined by three commonly used objective functions. We propose an integer programming formulation based on a

Abstract We consider strategic pricing problems in which each firm chooses between a non-cooperative (individual pricing) strategy and a cooperative (price negotiation) strategy. We first analyze a monopoly supply chain involving a supplier and a retailer, and then investigate two competing supply chains each consisting of a supplier and a retailer. We find that an appropriate power allocation between

Abstract Many complex engineering devices experience multiple dependent degradation processes. For each degradation process, there may exist substantial unit-to-unit heterogeneity. In this paper, we describe the dependence structure among multiple dependent degradation processes using copulas and model unit-level heterogeneity as random effects. A two-stage estimation method is developed for statistical

Abstract Since September 11, 2001, the United States has invested a significant amount of resources into improving aviation security operations, with the Transportation Security Administration (TSA) assuming the responsibilities for security policy-making at commercial airports. This article reviews the literature that supports policies for risk-based passenger screening procedures and chronicles the

Abstract With significant economic and environmental benefits, renewable energy is increasingly used to generate electricity. To hedge against the uncertainty due to the increasing penetration of renewable energy, an ancillary service market was introduced to maintain reliability and efficiency, in addition to day-ahead and real-time energy markets. To co-optimize these two markets, a unit commitment

Abstract We consider a stochastically deteriorating system with self-announcing failures that require immediate reactive replacement. For such a system, we consider an age-replacement policy (without minimal repair) under which the system is replaced at failure (reactive replacement) or at a prescribed replacement time (preventive replacement), whichever occurs first. Motivated by factors such as decreasing

Multi-state series-parallel systems are widely-used for representing engineering systems. In real-life cases, engineers need to select an optimal system structure among many different multi-state series-parallel system structures. Screening of system structures is meaningful and critical. Moreover, to design a reliable structure, reliability evaluation is an indispensable part. Due to the large number

Abstract We propose optimal preventive maintenance strategies for n-component coherent systems. We assume that in the early time of the system operation all failed components are repaired, such that the state of a failed component gets back to a working state, worse than that of prior to failure. To modeling this repair action, we utilize a counting process on the interval (0,τ], known as generalized

Abstract Applications of cloud computing are increasing as companies shift from on-premise IT environments to public, private, or hybrid clouds. Consequently, cloud providers use capacity planning to maintain the capacity of computing resources (instances) required to meet the dynamic nature of the demand (queries). However, there is a trade-off between deploying too many costly instances, and deploying

Abstract Shortening the lead time for product development (PD) provides enterprises with a competitive advantage. Given the iterative nature of PD projects, two aspects are regularly considered to shorten the PD lead time, that is, conducting faster or fewer iterations. However, executing faster iterations usually causes more iterations and vice versa. Therefore, suitable coordination between faster

Abstract In many emerging economies, callers may abandon ambulance requests due to a combination of operational (small fleet size), infrastructural (long travel times) and behavioral factors (low trust in the ambulance system). As a result, ambulance capacity, which is already scarce, is wasted in serving calls that are likely to be abandoned later. In this article, we investigate the design of an

Sampling plans play an important role in monitoring production systems and reducing quality- and maintenance-related costs. Existing sampling plans usually focus on one assignable cause. However, multiple assignable causes may occur especially for a multistage production system, and the resulting process shift may propagate downstream. This paper addresses the problem of finding the optimal sampling

This paper considers the preventive maintenance (PM) under a two-dimensional (2-D) warranty contract with time and usage limits. From a manufacturer’s point of view, we develop a dynamic maintenance model with a random horizon to include the impact of random and dynamic usage rates on PM decisions. The model treats the cumulative amount of usage as a state variable that provides information about the

Abstract In this study, we are primarily motivated by the research problem of recognizing heterogeneous customer behavior towards waiting for order fulfillment under the threshold rationing policy (also known as the critical level policy), and aim to find its effect on system stock levels and performance measures. We assume a continuous review one-for-one ordering policy with generally distributed

Robust parameter design (RPD) is a quality improvement method to mitigate the effect of input noise on system output quality via adjustment of control and signal factors. This paper considers RPD with multiple functional outputs and multiple target functions based on a time-consuming nonlinear simulator, which is a challenging problem rarely studied in the literature. The Joseph-Wu formulation of multi-target

Bathtub shaped failure intensity is typical for large-scaled repairable systems with a number of different failure modes. Sometimes, repairable systems may exhibit a failure pattern different from the traditional bathtub shape due to the existence of multiple failure modes. This study proposes two superposed Poisson process models with modified bathtub intensity functions to capture this kind of failure

Abstract With increasing availability of consumer data and rapid advancement and application of technologies, online retailers are gaining better knowledge of customers’ shopping behavior and preferences. Thus more and more retailers are providing personalized product assortment to better match the needs of customers and generate more sales. In this article, we study a two-stage revenue management

Abstract Infected individuals must be aware of disease symptoms to seek care, so outreach and education programs are critical to disease control. However, public health organizations often only have limited resources for outreach and must carefully design campaigns to maximize effectiveness, potentially leveraging word-of-mouth information spread. We show how classic epidemiological models can be reformulated