Unforeseen Disruptions Research Articles

A Heuristic for Inserting Randomly Arriving Jobs Into an Existing Hoist Schedule

Hoist scheduling in automated electroplating lines has been extensively studied in a static environment. However, practical electroplating lines are subject to diversified unforeseen disruptions that require frequent rescheduling to maintain or optimize system performance. This paper addresses a hoist scheduling problem, where randomly arriving jobs need to be inserted into an existing schedule without changing the sequence of hoist moves already scheduled. The objective is to minimize the total completion time of all the jobs in the existing schedule and a newly inserted job. We develop a polynomial-time heuristic that adjusts the starting times of the existing hoist moves to a limited extent but does not bring about a severe disturbance of the existing hoist moves. We compare our algorithm with two existing approaches with different rescheduling policies (i.e., partial and zero adjustment of the existing schedule). We empirically analyze the productivity and the stability of the schedules generated by the three approaches. Computational results demonstrate that our algorithm can generate more productive and stable schedules than the two existing approaches. Note to Practitioners —Electroplating and chemical surface treatment lines with automated material handling hoists are commonplace in electronics, semiconductor, and many other manufacturing industries. In an uncertain environment, hoist rescheduling plays an important role in improving the productivity and reducing the impact of disruptions. This paper presents a hoist scheduling algorithm to deal with dynamic job arrivals by considering the impact of the disturbance incurred by rescheduling. Our algorithm can generate a better schedule with smaller total completion time and slighter disturbance than the existing algorithms. The proposed algorithm runs in polynomial time and can be used to control hoist operations in practical electroplating lines. A comparative analysis provides useful insights on the implementation of rescheduling approaches and policies to industry practitioners.

An agent-based simulation system for multi-project scheduling under uncertainty

This work proposes an agent-based simulation system to address challenges in resource constrained multi-project scheduling under uncertainty. The system aims at helping users develop robust schedules by taking care of intra- and inter-dependencies between projects, conflicting demands for limited resources, and the potential knock-on effect of unpredictable events. With the interactive graphical user interface embedded in the system, users are enabled to investigate project process, evaluate modified schedule, forecast impact resulted from unexpected disruptions, and conduct various what-if analysis. Reactive and proactive scheduling algorithms have been developed in the simulation system to resolve unforeseen disruptions and increase the robustness of the solutions. Experiments on a real-world case study of a technology-intensive industrial product development program have been conducted to evaluate the effectiveness of the proposed algorithms.

Quantitative metrics to analyze supply chain resilience and associated costs

The growth of global supply chains has allowed trading partners to experience synergistic, economic expansion and increase their competitive success. At the same time, reliance on global supply chains exposes its trading partners to unforeseen disruptions. While the economic benefits are tremendous, they are not without risk as global supply chains are by their very nature susceptible to a wide array of disruptions. Methods that mitigate the effect of disruption directly contribute to the competitive success of global supply chain networks. One approach for mitigating the effects of disruption is to increase resilience. Thus, this research focuses on understanding supply chain vulnerability and how to return the supply chain to its desirable performance level after a disruptive event by reconfiguring the supply chain network. This article frames this foundational work in the context of systems theory to add to the body of resilience research by providing a time-dependent definition of supply chain resilience. This article then provides a mathematical model, based on inventory theory that operationalizes that definition. The model is presented in the context of a multi-echelon, post-production support network of a sustainment-dominated system such as those found in the aerospace, defense, utilities, and construction industries. The model demonstrates the post-disruption resilience at each supply chain network node along with the investment necessary to restore the network.

Template-based re-optimization of rolling stock rotations

Rolling stock, i.e., the set of railway vehicles, is among the most expensive and limited assets of a railway company and must be used efficiently. We consider in this paper the re-optimization problem to recover from unforeseen disruptions. We propose a template concept that allows to recover cost minimal rolling stock rotations from reference rotations under a large variety of operational requirements. To this end, connection templates as well as rotation templates are introduced and their application within a rolling stock rotation planning model is discussed. We present an implementation within the rolling stock rotation optimization framework rotor and computational results for scenarios provided by DB Fernverkehr AG, one of the leading railway operators in Europe.

Ebola and Global Airline Business: An Integrated Framework of Companies’ Responses to Adverse Environmental Shock

In spite of a growing body of literature on risk management, our understanding of how companies respond to unforeseen disruptions such as pandemics or outbreaks remains limited. This study advances tourism management, operations strategy, and risk management research by examining how airlines have responded to the Ebola outbreak in West Africa. Using archival records, the study uncovered three unique stages in airlines’ responses to the outbreak. The study provides insights and rationale behind strategic persistence and downscaling approaches adopted by different airlines. The implications for risk management and public policy are examined. © 2016 Wiley Periodicals, Inc.

Dealing with the unexpected: Using latent structures for efficiency and resilience

In order to be effective, many organizations need to combine an ability to operate efficiently with an ability to deal with unforeseen disruptions (resilience). We explore how organizations can manage this efficiency-resilience challenge by complementing their primary structures (designed for efficiency) with flexible, latent structures that lie “beneath the surface” and become activated when they face a disruption. Specifically, we explore what type of latent structures organizations need to master in order to be capable of dealing with various types of disruptions. In addition, we conceptually explore two switching mechanisms that can allow organizations to quickly recognize the need for activating a latent structure and, subsequently, orchestrate such an effort. All in all, this manuscript advances new knowledge on the antecedents and mechanisms that may enable organizational efficiency and resilience.

Impact of Resource Sharing in Manufacturing on Logistical Key Figures

Increasing fluctuations in demand or unforeseen disruptions have a disturbing impact on logistical key figures of manufacturing companies. Common countermeasures, e.g. the increase of the production capacity by adding new machines, always lead to improvements of single key figures while worsening others simultaneously. In the light of increasing fluctuations in manufacturing, new approaches have to be considered. We propose the utilization of resource sharing for manufacturing companies as a possible solution in analogy to shared loads in transport logistics. In this context, we refer to production machines as shared resources. Each cooperating company allows others to access its manufacturing resources according to a cooperation agreement. This concept empowers companies to deal with the disturbing events by distributing orders to cooperation partners instead of maintaining safety capacities or redundant systems. In this paper we discuss the opportunities and impediments of shared resources in the area of production enterprises. We further provide an outlined concept for its implementation into practice with respect to technological innovations on the one hand and practical requirements on the other hand. Our argumentation is supported by a simulation study, which quantifies the impact of resource sharing on logistical key figures.

Toward quantifying metrics for rail-system resilience: identification and analysis of performance weak resilience signals

This paper aims to enhance tangibility of the resilience engineering concept by facilitating understanding and operationalization of weak resilience signals (WRSs) in the rail sector. Within complex socio-technical systems, accidents can be seen as unwanted outcomes emerging from uncontrolled sources of entropy (functional resonance). Various theoretical models exist to determine the variability of system interactions, the resilience state and the organization's intrinsic abilities to reorganize and manage their functioning and adaptive capacity to cope with unexpected and unforeseen disruptions. However, operationalizing and measuring concrete and reliable manifestations of resilience and assessing their impact at a system level have proved to be a challenge. A multi-method, ethnographic observation and resilience questionnaire, were used to determine resilience baseline conditions at an operational rail traffic control post. This paper describes the development, implementation and initial validation of WRSs identified and modeled around a `performance system boundary.' In addition, a WRS analysis function is introduced to interpret underlying factors of the performance WRSs and serves as a method to reveal potential sources of future resonance that could comprise system resilience. Results indicate that performance WRSs can successfully be implemented to accentuate relative deviations from resilience baseline conditions. A WRS analysis function can help to interpret these divergences and could be used to reveal (creeping) change processes and unnoticed initiating events that facilitate emergence that degrades rail-system resilience. Establishing relevant change signals in advance can contribute to anticipation and awareness, enhance organizational learning and stimulate resilient courses of action and adaptive behavior that ensures rail operation reliability.

The deterioration of production schedules during unforeseen disruptions

In most real-world environments, production scheduling is an ongoing process where the presence of a variety of unforeseen disruptions is usually inevitable, and continually forces reconsideration and revision of pre-established schedules. Many of the approaches developed to solve the problem of production scheduling are often unfeasible in real-world, and near-optimal schedules with respect to the estimated data may become obsolete when they are released to the production lines or shop floor. This paper outlines the impact of unforeseen disruptions that affect manufacturing systems during production, and being able to cope or react to this determines a company's output and profitability. The theories of multifactor productivity and line balancing are employed to determine how disruptions affect productivity output and the result reveals that when disruptions occur continuously with time, the total productivity output decreases as time goes on and, on the other hand, total production time increases and requires more resources to meet the planned capacity demand (PCD).

The Effect of Unforeseen Disruption on Different Types of Manufacturing Industry-Layout

Consistency and on timely delivery are among some of the factors that can keep a customer loyal and committed to a manufacturing industry. Almost all manufacturing facilities need to use production scheduling systems to increase productivity, reduce production costs and time. Most manufacturing industries invest huge amount of money to manufacture and supply products on time in order to meet customers demand and objectives but due to unforeseen disruptions, these objectives are difficult to achieve. In Real-life, production operations are subject to a large number of unexpected disruptions that may invalidate an original schedule. Being able to cope or react to these disruptions determines a company’s out-put and profitability. Productivity expression and simulation models are employed to assist in determining operational characteristics and also by comparing results from undisrupted system with that which is disrupted. These proposed models are tested on different tile manufacturing industry lay-outs in CMR and it is demonstrated that the leading source of disruption varies with different industry-layout and geographical regions. The study revealed that, the most common cause of disruption are power failure, machine breakdown, advert whether and employees absenteeism).This can be concluded from an industrial engineering point of view that, disruption during tile manufacturing is the main cause of low productivity or out-put in CMR tile manufacturing industries.

Data Analysis of Delays in Airline Networks

Cost-optimized airline resource schedules often imply a lack of delay tolerance in case of unforeseen disruptions, e.g. late check-ins, technical defects or airport and airspace congestion. Therefore, the consideration of timeliness and robustness has become an important topic in robust resource scheduling and a wide range of sophisticated scheduling approaches has been developed in recent years. However, these approaches depend on assumptions made concerning delay occurrences. A better understanding of delay mechanisms may lead to a better trade-off between cost-efficiency and robustness and is therefore the purpose of this paper. We provide a data-driven detection of decision rules for daytime delay trends, depending on spatio-temporal attributes. The focus is on interpretable rules whose prediction accuracy is compared to random forests as a non-parametric, automated modeling approach. The obtained results give an insight into both the nature of primary delay occurrence and the methodical potential of delay prediction in the context of robust resource scheduling.

Measuring Workload Weak Resilience Signals at a Rail Control Post

OCCUPATIONAL APPLICATIONS This article describes an observational study at a rail control post to measure workload weak resilience signals. A weak resilience signal indicates a possible degradation of a system's resilience, which is defined as the ability of a complex socio-technical system to cope with unexpected and unforeseen disruptions. A method based upon a weak resilience signal framework introduces a new metric, stretch, to measure the signals. Stretch is a subjective or an objective reaction of the system to an external cluster event and is an operationalization of variables in an earlier stress–strain model. The stretch ratio between the subjective and objective stretch are used to identify workload weak resilience signals. Weak resilience signals identified during real-time operation revealed obstacles that influence the resilience state and enabled actions to anticipate and mitigate changes to maintain the resilience of the system.TECHNICAL ABSTRACT Background: Continuous performance improvement of a complex socio-technical system may result in a reduced ability to cope with unexpected and unforeseen disruptions. As with technical and biological systems, these socio-technical systems may become “robust, yet fragile.” Resilience engineering examines the ability of a socio-technical system to reorganize and adapt to the unexpected and unforeseen. However, the resilience doctrine is not yet sufficiently well developed for designing and achieving those goals, and metrics are needed to identify resilience change. Purpose: A new approach was explored to identify changes in the resilience of a rail system around the workload boundary to anticipate those changes during normal operations and hence improve the ability to cope with unexpected and unforeseen disruptions. Methods: A weak resilience signal framework was developed with a resilience-state model for a railway system, resulting in a generic, quantifiable, weak resilience signal model. Two workload measurements (i.e., external cognitive task load and integrated workload scale) were combined into a new metric called stretch. Heart rate variability was used for correlation and validation. An observational study was used to measure workload weak resilience signal through workload quantification at an operational rail control post. Results: A theoretical resilience-state model for a railway system was developed and used to generate a generic quantifiable weak resilience signal model, forming a weak resilience signal framework that is the basis for a method to measure workload weak resilience signal through a new metric called stretch with three variations: objective stretch, subjective stretch, and stretch ratio. A component of the subjective stretch is the integrated workload scale, for which a real-time tool was developed for measuring and monitoring. Workload weak resilience signals identified at a rail control post triggered analysis to reveal anticipated obstacles. Conclusions: A resilience-state model of a rail system can be used to quantify workload weak resilience signals. Stretch ratio differences represent changes of the workload state used to measure workload weak resilience signals that aid in revealing obstacles jeopardizing the resilience state.

An improved method for managing catastrophic supply chain disruptions

This article analyzes the differences between frequent and rare risks for supply chain disruptions, and proposes a new, improved risk measurement and prioritization method to account for the characteristics of rare risks. The varying idiosyncrasies of decision makers are integrated into this method such that risk management can be brought into alignment with an individual manager's preferences. Also woven into this tapestry is the notion of detection, which is familiar to those who have applied failure modes and effects analysis (FMEA), but novel in the arena of supply chain risk management. Rare risks in the supply chain are, by their nature, unsettling: unforeseen disruptions are always present, probability estimates are imprecise, and comprehensive data collection is impossible. These difficulties are taken into account by the presented risk management framework. While the proposed ordinal scales are perhaps unsettling to many who desire greater precision, measurement methods must fit the precision that is possible. By considering rare risks along with frequent risks, managers can be better positioned to deal with the unforeseen.

A secure and efficient inventory management system for disasters

An efficient humanitarian inventory control model and emergency logistics system plays a crucial role in maintaining reliable flow of vital supplies to the victims located in the shelters and minimizing the impacts of the unforeseen disruptions that can occur. This system should not only allow the efficient usage and distribution of emergency supplies but should also offer the ability to be integrated with emerging ITS technologies such as Radio Frequency Identification Devices (RFIDs) for commodity tracking and logistics. This paper proposes a comprehensive methodology for the development of a humanitarian emergency management framework based on the real-time tracking of emergency supplies and demands through the use of RFID technology integrated with a multi-commodity stochastic humanitarian inventory management model (MC-SHIC). First, logistics and management aspects of RFID technologies in the context of the emergency disaster relief framework are discussed. Then, MC-SHIC model proposed to determine the optimal emergency inventory levels to prevent possible disruptions at the minimal cost is presented. The solution of the model with several sensitivity analyses obtained using the pLEPs algorithm is presented and discussed. Realizing that actual emergency inventory levels can deviate from optimal values during the actual disaster relief period due to the possible stochastic disruptions such as fluctuating demand for vital supplies in the shelters, a comprehensive on-line inventory control framework is proposed to minimize impacts of these unforeseen disruptions, or at least to address the problem at hand as fast as possible. Within this methodology, we obtain an approximation of the MC-SHIC model using a simultaneous perturbation stochastic approximation (SPSA) based functional approximator, and compare the performance of these algorithms for solving the new unconstrained optimization problem. Finally, proposed model-free on-line control methodology is discussed using examples to understand the efficiency and practicality of both algorithms in terms of computational times and accuracy of results.

Control Rights, Network Structure and Vertical Integration: Evidence from Regional Airlines

This paper investigates the relationship between vertical integration and the importance of control rights under incomplete contracts. Our setting is the U.S regional airline industry. Regional airlines operate flights for major carriers under the major's brand. The majors market the regionals' flights as their own. There is substantial heterogeneity in whether or not regionals are owned by the major for which they operate. Furthermore, several majors own some of their regional partners while also contracting with others. We develop a simple framework that illustrates the benefits and costs of vertical integration between a major and regional. We argue that when unforeseen disruptions create the need for schedule adjustments - as frequently occurs in the airline industry - the major will internalize the impact of the disruption on its entire network, while the regional will not. Ownership of a regional mitigates this incentive problem by giving the major rights of control over how the regional's physical assets and labor force are used. However, by bringing the regional's labor force in-house, ownership of a regional may erode some of the labor cost savings that are very reason why majors subcontract certain flights to regionals. Using data on majors' use of regionals in the second quarter of 2000, we test whether majors' choice of organizational form reflects this tradeoff between greater control and lower labor costs. Our results provide support for our analytical framework. We find that owned regionals are more likely to serve city pairs that are (1) more integrated into the major's network, where externalities not internalized by the regional will be the greatest; and (2) that owned regionals are more likely to serve city pairs with adverse weather conditions, where unforeseen schedule disruptions will be more common.

Economic Security and the Myth of the Efficiency/Equity Tradeoff

Confronted with an uncertain future driven by heightened global competition, rapid technological change, and volatile energy prices, a growing number of managers have responded by becoming more flexible in their use of resources. For example, their firms have increased the use of temporary employees, adopted just-in-time production systems, and grouped people into work teams that can be reorganized rapidly as business conditions change. What these strategies have in common is the conversion of fixed into variable costs, which helps insulate profits against unforeseen disruptions in business conditions. This preference for flexibility is even stronger for financing and investment decisions. For example, because most financial transactions occur in an environment characterized by asymmetric information, investors prefer liquid securities and engage in practices such as the sequential financing of venture capital deals. Moreover, many executives have begun to treat capital project proposals as a series of real options, enabling them to gauge how improvements in the timing of investment expenditures can increase the firm's value. The way these practices reduce uncertainty is by shortening the investment time horizon, which is crucial for companies that must invest in long-term, often irreversible assets. Neoclassical economists support this quest for flexibility on the presumption that it improves allocative efficiency, despite the fact that it usually increases wage and employment insecurity. However, as Glen Atkinson noted, the tradeoff between equity and

Executing production schedules in the face of uncertainties: A review and some future directions

We review the literature on executing production schedules in the presence of unforeseen disruptions on the shop floor. We discuss a number of issues related to problem formulation, and discuss the functions of the production schedule in the organization and provide a taxonomy of the different types of uncertainty faced by scheduling algorithms. We then review previous research relative to these issues, and suggest a number of directions for future work in this area.

F-0617 階層分散型生産システムにおけるリアクティブスケジューリング : GAの適用(S42-3 生産システムにおけるソフトウェア技術(3))(S42 生産システムにおけるソフトウェア技術)

Production scheduling tasks are carried out hierarchically and concurrently, such as production scheduling for manufacturing systems, for factories and for shops, by different persons and/or organizations. Therefore, a systematic procedure is eagerly required to change the production schedules and to keep the consistency among the hierarchical scheduling tasks, when some unforeseen disruptions occur in the manufacturing systems. A rescheduling method is proposed to change the production schedules and to keep the consistency among the production schedules of the hierarchical and decentralized manufacturing systems. A prototype of distributed reactive scheduling system for the hierarchical and decentralized manufacturing systems is developed and applied to the consistency management problems in the rescheduling tasks.

Multi-Objective Modelling of Manufacturing Systems. 3rd Report. Concurrent Approach of Rescheduling on Hierarchical and Decentralized Manufacturing Systems.

Production scheduling tasks are in general carried out hierarchically and concurrently, such as scheduling for manufacturing systems, for factories and for shops, by different persons and/or organizations. Therefore, a systematic procedure is eagerly required to change the schedules and to keep the consistency among the hierarchical scheduling tasks, when some unforeseen disruptions occur in the manufacturing systems. The objectives of the research are to establish a systematic method for supporting the rescheduling tasks and for keeping the consistency among the various layers of schedules of the hierarchical and decentralized manufacturing systems. Models for hierarchical production schedules are proposed, and rescheduling procedures are also developed based on the models. A rescheduling method is proposed to change the schedules and to keep the consistency among the schedules. A prototype of hierarchical and concurrent rescheduling system is developed and applied to the consistency management problems in the rescheduling tasks.

A Price-Directed Approach to Real-Time Scheduling of Production Operations

Abstract Most past approaches to job shop scheduling are either highly myopic, or they are unable to adapt effectively to the stream of unforeseen disruptions that characterizes almost all manufacturing systems. We propose a two-module scheduling system that is both robust and non-myopic. Periodically a Planning Module develops a global view of what is likely to happen in die facility over the next one to four weeks. It then passes information down to the Dispatching Module. The Dispatching Module is based on microprocessors that are located on the factory floor. Whenever a machine is about to become idle, a fast optimization algorithm is run on the closest microprocessor to decide which job should be done next. The data provided by the Planning Module allows this decision to be made in a non-myopic manner.