1,720,999 research outputs found
A branch-and-bound approach to schedule a no-wait flow shop to minimize the CVaR of the residual work content
Full text linkThe aerospace industry ranks among the largest manufacturing industries in the world facing a significant growing phase as well as an increased competition. This paper addresses the scheduling of a set of jobs in a paced assembly line in presence of uncertainty affecting the availability of production resources, stemming from the assembly process in the aircraft manufacturing industry. The production problem is modeled as a no-wait paced permutation flow shop and solved providing a robust scheduling solution minimizing the conditional value-at-risk (CVaR) of the residual work content, i.e., the amount of workload that cannot be completed during the cycle time in the stations, due to a lack of available resources. A branch-and-bound approach is developed and applied to randomly generated instances as well as to an industrial problem related to the production of aircrafts
A branch-and-bound approach to minimise the value-at-risk of the makespan in a stochastic two-machine flow shop
Full text linkPlanning and scheduling approaches in real manufacturing environments entail the need to cope with random attributes and variables to match the characteristics of real scheduling problems where uncertain events are frequent. Moreover, the capability of devising robust schedules, which are less sensitive to the disruptive effects of unexpected events, is a major request in real applications. In this paper, a branch-and-bound approach is proposed to solve the two-machine permutation flow shop scheduling problem with stochastic processing times. The objective is the minimisation of the value-at-risk of the makespan, to support decision-makers in the trade-off between the expected performance and the mitigation of the impact of extreme scenarios. A Markovian Activity Network (MAN) model is adopted to estimate the distribution of the makespan and assess the value-at-risk for both partial and complete schedules. Phase-type distributions are used to enable general distributions for processing times while maintaining the capability to exploit a Markovian approach. The effectiveness and performance of the proposed approach are demonstrated through a set of computational experiments
An upper bound for the inter-exit time of two jobs in an m-machine flow shop
Full text linkThis paper addresses the class of permutation flow shop scheduling where jobs, after their completion, must be grouped in batches. This is a common scheme in industrial environments, where products undergo multiple process steps in different shops and, when completed, must be transported to customers or the next production step. A new optimisation criterion is used, the inter-exit time, i.e., the difference between the completion times of two jobs. An upper bound is proposed and demonstrated for a general permutation flow shop with m machines
Robust scheduling in a two-machine re-entrant flow shop to minimise the value-at-risk of the makespan: branch-and-bound and heuristic algorithms based on Markovian activity networks and phase-type distributions
Full text linkThis paper addresses a two-machine re-entrant flow shop scheduling problem with stochastic processing times where each job is expected to require a rework phase, flowing twice within the whole system. Due to the stochastic characteristics of the addressed problem, the proposed approach aims to devise robust schedules, i.e., schedules that are less sensitive to the occurrence of uncertain events, specifically, to the variability of the processing times. Two classes of approaches are proposed: the first is a branch-and-bound algorithm capable of solving the problem optimally, although with limitations regarding the size of the scheduling instances; the second is heuristic algorithms that can be applied to medium/large instances. For both approaches, the goal is to minimise the value-at-risk associated with the makespan, to assist decision-makers in balancing expected performance and mitigating the impact of extreme scenarios. A Markovian Activity Network (MAN) model is exploited to estimate the distribution of the makespan and evaluate its value-at-risk. Phase-type distributions are used to cope with general distributions for the processing times while exploiting a Markovian approach. A set of computational experiments is conducted to demonstrate the effectiveness and performance of the proposed approaches
Formal modelling of release control policies as a plug-in for performance evaluation of manufacturing systems
Full text linkControl policies significantly affect the performance of manufacturing systems, driving the need to assess their impact during both the design and operational phases. Performance evaluation tools can provide a relevant support, but their full exploitation is hindered by the difficulty of considering the huge variety of control decisions that are interwoven with manufacturing system configurations. Herein, a formal modelling approach is presented to jointly describe a manufacturing system and its release control policies, thus enabling the definition of performance evaluation models in terms of different policies. An application case is provided for the automatic generation of discrete event simulation models to assess the viability of the approach for assembly lines
A branch-and-bound approach for the single machine maximum lateness stochastic scheduling problem to minimize the value-at-risk
Full text linkThe research in the field of robust scheduling aims at devising schedules which are not sensitiveto a certain extentto the disruptive effects of unexpected events. Nevertheless, the protection of the schedule from rare events causing heavy losses is still a challenging aim. The paper presents a novel approach for protecting the quality of a schedule by assessing the risk associated to the different scheduling decisions. The approach is applied to a stochastic scheduling problem with a set of jobs to be sequenced on a single machine. The release dates and processing times of the jobs are generally distributed independent random variables, while the due dates are deterministic. A branch-and-bound approach is taken to minimise the value-at-risk of the distribution of the maximum lateness. The viability of the approach is demonstrated through a computational experiment and the application to an industrial problem in the tool making industry
A scheduling approach for chemical vapour deposition processes in the production of semiconductors
Full text linkThe production of semiconductors for applications in microelectronics is operated through photo-lithographic and chemical processes whereof Chemical Vapor Deposition (CVD) technology is one of the most used. CVD processes need to operate in furnaces under controlled atmosphere and, every time the furnace is accessed from the external environment, a purging time is needed to restore the prescribed atmosphere. The optimisation of the utilisation of the furnaces depends on the sequencing of loading and unloading operations entailing the need to disturb the controlled atmosphere. We propose the use of a disaggregated time formulation based on step variables to model a scheduling problem aiming at identifying the optimal sequence of operations and supporting the definition of optimal dispatching policies
An approach for the robust design of a reconfigurable assembly cell with 7-axis robot
Full text linkThe increasing variety of products and the variability of the demand are pushing manufacturing companies in a challenging and competing environment. These trends affect many industrial sectors, including the automotive one, impacting the whole supply chain, including the production of spare parts. The automotive spare part’s market is aimed at providing replacing parts during the whole life cycle of cars. As the design of cars becomes more and more sophisticated, producing spare parts requires complex production processes, a wide range of different technologies and the need to cope with different materials. In this context, the design of assembly systems and proper management policies have a considerable importance for the competitiveness of spare parts suppliers. In this paper, a configuration approach is proposed, to select a robust design solution for a reconfigurable assembly cell. The solution consists of an initial configuration together with a set of alternative reconfiguration plans to cope with the intrinsic uncertainty of the spare part manufacturing requirements. An innovative reconfigurable assembly cell architecture is exploited, while robustness is pursued by minimising a function of the risk associated with investment and operational costs of the assembly cell. The viability of the proposed approach is demonstrated through the application to an industrial case
An Approximate Approach for the Verification of Process Plans with an Application to Reconfigurable Pallets
No full textThe manufacturing sector has to be able to manage high-variety and low-volumes per product, causing the adoption of a dedicated production system/cell to be unfeasible. In this context, reconfigurable pallets and flexible fixtures are enablers to manage product variety and volume variability. Namely, as a pallet is reconfigured, the associated part program needs to be verified to check for possible collisions between the tools and the new machining environment. An approach is proposed to verify the machinability of a pallet configuration given an existing part program. The approach grounds on an approximated collision check method exploiting a 3D representation of the machining environment (fixtures and parts). The approach is validated through an application to a realistic use case and the comparison with the results of a traditional collision check approach
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