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| 2. |
- Fotedar, Sunney, 1989
(författare)
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Mathematical Multi-Objective Optimization of the Tactical Allocation of Machining Resources in Functional Workshops
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In the aerospace industry, efficient management of machining capacity is crucial to meet the required service levels to customers and to maintain control of the tied-up working capital. We introduce new multi-item , multi-level capacitated resource allocation models with a medium--to--long--term planning horizon. The model refers to functional workshops where costly and/or time- and resource-demanding preparations (or qualifications) are required each time a product needs to be (re)allocated to a machining resource. Our goal is to identify possible product routings through the factory which minimize the maximum excess resource loading above a given loading threshold while incurring as low qualification costs as possible and minimizing the inventory. In Paper I , we propose a new bi-objective mixed-integer (linear) optimization model for the Tactical Resource Allocation Problem (TRAP). We highlight some of the mathematical properties of the TRAP which are utilized to enhance the solution process. In Paper II , we address the uncertainty in the coefficients of one of the objective functions considered in the bi-objective TRAP. We propose a new bi-objective robust efficiency concept and highlight its benefits over existing robust efficiency concepts. In Paper III , we extend the TRAP with an inventory of semi-finished as well as finished parts, resulting in a tri-objective mixed-integer (linear) programming model. We create a criterion space partitioning approach that enables solving sub-problems simultaneously. In Paper IV , using our knowledge from our previous work we embarked upon a task to generalize our findings to develop an approach for any discrete tri-objective optimization problem. The focus is on identifying a representative set of non-dominated points with a pre-defined desired coverage gap .
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| 3. |
- Eriksson, T., et al.
(författare)
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Successive Encoding of Correlated Sources
- 1982
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The encoding of a discrete memoryless multiple source for reconstruction of a sequence with is considered. We require that the encoding should be such that is encoded first without any consideration of , while in a seeond part of the encoding this latter sequence is encoded based on knowledge of the outcome of the first encoding. The resulting scheme is called successive encoding. We find general outer and inner bounds for the corresponding set of achievable rates along with a complete single letter characterization for the special case . Comparisons with the Slepian-Wolf problem [3] and the Ahlswede-Körner-Wyner side information problem [2 ], [9) are carried out.
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| 4. |
- Fotedar, Sunney, 1989, et al.
(författare)
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Mathematical optimization of the tactical allocation of machining resources for an efficient capacity utilization in aerospace component manufacturing
- 2019
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Ingår i: Proceedings of the 10th Aerospace Technology Congress. - : Linköping University Electronic Press. - 1650-3686 .- 1650-3740. - 9789175190068 ; , s. 183-188
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Konferensbidrag (refereegranskat)abstract
- In the aerospace industry, with low volumes and many products, there is a critical need to efficiently use available manufacturing resources. Currently, at GKN Aerospace, resource allocation decisions that in many cases will last for several years are to some extent made with a short-term focus so as to minimize machining time, which results in a too high load on the most capable machines, and too low load on the less capable ones. This creates an imbalance in capacity utilization that leads to unnecessary queuing at some machines, resulting in long lead times and in an increase in tied-up capital. Tactical resource allocation on the medium to long-range planning horizon (six months to several years) aims to address this issue by allocating resources to meet the predicted future demand as effectively as possible, in order to ensure long range profitability. Our intent is to use mathematical optimization to find the best possible allocations.
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| 5. |
- Obradovic, Gabrijela, 1994, et al.
(författare)
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Simultaneous scheduling of replacement and repair of common components in operating systems A multi-objective mathematical optimization model
- 2022
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Ingår i: Annals of Operations Research. - : Springer Science and Business Media LLC. - 0254-5330 .- 1572-9338. ; 322, s. 147-65
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Tidskriftsartikel (refereegranskat)abstract
- In order for a system to stay operational, its components need maintenance. We consider two stakeholders-a system operator and a maintenance workshop-and a contract governing their joint activities. Components in the operating systems that are to be maintained are sent to the maintenance workshop, which should perform all maintenance activities on time in order to satisfy the contract. The maintained components are then sent back to be used in the operating systems. Our modeling of this system-of-systems includes stocks of damaged and repaired components, the workshop scheduling, and the planning of preventive maintenance for the operating systems. Our modeling is based on a mixed-binary linear optimization (MBLP) model of a preventive maintenance scheduling problem with so-called interval costs over a finite and discretized time horizon. We generalize and extend this model with the flow of components through the workshop, including the stocks of spare components. The resulting scheduling model-a mixed-integer optimization (MILP) model-is then utilized to optimize the main contract in a bi-objective setting: maximizing the availability of repaired (or new) components and minimizing the costs of maintaining the operating systems over the time horizon. We analyze the main contract and briefly discuss a turn-around time contract. Our results concern the effect of our modeling on the levels of the stocks of components over time, in particular minimizing the risk for lack of spare components.
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| 6. |
- Åblad, Edvin, 1991, et al.
(författare)
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Exact makespan minimization of unrelated parallel machines
- 2021
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Ingår i: Open Journal of Mathematical Optimization. - : Cellule MathDoc/CEDRAM. - 2777-5860. ; 2
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Tidskriftsartikel (refereegranskat)abstract
- We study methods for the exact solution of the unrelated parallel machine problem with makespan minimization, generally denoted as R||Cmax. Our original application arises from the automotive assembly process where tasks needs to be distributed among several robots. This involves the solutions of several R||Cmax instances, which proved hard for a MILP solver since the makespan objective induces weak LP relaxation bounds. To improve these bounds and to enable the solution of larger instances, we propose a branch–and–bound method based on a Lagrangian relaxation of the assignment constraints. For this relaxation we derive a criterion for variable fixing and prove the zero duality gap property for the case of two parallel machines. Our computational studies indicate that the proposed algorithm is competitive with state-of-the-art methods on different types of instances. Moreover, the impact of each proposed feature is analysed.
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| 8. |
- Fotedar, Sunney, 1989, et al.
(författare)
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A decision-making tool to identify routings for an efficient utilization of machining resources: the decision makers’ perspective
- 2020
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Ingår i: PLANs forsknings-och tillämpningskonferens.
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Konferensbidrag (refereegranskat)abstract
- In the aerospace industry, efficient management of machining capacity is crucial to meet the required service levels to customers (which includes, measures of quality and lead-times ) and keeps the tied-up working capital in check. The proposed decision-making tool, described in this paper, aims to combine information and knowledge of manufacturing and logistics experts in a company to improve flow of materials through the factory. The material flow situation is different for a large aerospace tier-1 supplier as opposed to flow-based manufacturing company; when there is no pandemic or natural calamity, having relatively stable demand due to long-term contract is common, but there exists short-term demand variability. There is a complex flow of products at GKN Aerospace, as the products share machining resources, thus, resulting in uneven loads at machines and sometimes excess loading at certain machines. This along with short-term demand variability results in long queues in-front of machines which contributes with the biggest share of the total lead-time. Thus, long waiting times at one/many machine/s is common and may lead to bottlenecks in many places in the production pipeline. So, there is potential benefit in having rerouting-flexibility for products which can help in reducing queuing. However, qualifying a product for a new machine is time-consuming activity, and thus, should be done few years in advance. We propose a mathematical model aimed at improving some of these deficiencies of commonly used methods by facilitating balanced resource loading levels, i.e. to provide more degrees of freedom to the planner to absorb demand variations. The output provided by the model includes production routings in each time period (quarter) for the next 4–5 years; new qualifications to be done by technical staff for allocation of part types/products to machines which are not yet qualified/used for a given product. We keep the resource loading levels that are above a given threshold as low as possible and reduce the time/money spent for qualifying new allocations.
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| 9. |
- Fotedar, Sunney, et al.
(författare)
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Robust optimization of a bi-objective tactical resource allocation problem with uncertain qualification costs
- 2022
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Ingår i: Autonomous Agents and Multi-Agent Systems. - : Springer Science and Business Media LLC. - 1387-2532 .- 1573-7454. ; 36:2
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Tidskriftsartikel (refereegranskat)abstract
- In the presence of uncertainties in the parameters of a mathematical model, optimal solutions using nominal or expected parameter values can be misleading. In practice, robust solutions to an optimization problem are desired. Although robustness is a key research topic within single-objective optimization, little attention is received within multi-objective optimization, i.e. robust multi-objective optimization.This work builds on recent work within robust multi-objective optimization and presents a new robust efficiency concept for bi-objective optimization problems with one uncertain objective. Our proposed concept and algorithmic contribution are tested on a real-world multi-item capacitated resource planning problem, appearing at a large aerospace company manufacturing high precision engine parts. Our algorithm finds all the robust efficient solutions required by the decision-makers in significantly less time than the approach of Kuhn et al. (Eur J Oper Res 252(2):418-431, 2016) on 28 of the 30 industrial instances.
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| 10. |
- Thörnblad, Karin, 1971, et al.
(författare)
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Scheduling optimization of a real flexible job shop including fixture availability and preventive maintenance
- 2015
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Ingår i: European Journal of Industrial Engineering. - 1751-5254. ; 9:1, s. 126-145
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Tidskriftsartikel (refereegranskat)abstract
- The multitask cell at GKN Aerospace Sweden is a flexible job shop containing ten resources aimed at being flexible with regard to product mix and processing types. We present a time-indexed formulation of the problem of optimally scheduling the planned jobs on the resources, also considering a limited availability of fixtures as well as required preventive maintenance activities. The objective is to minimize a weighted sum of the completion times and tardiness for the jobs, where the tardiness weight for a given job is a non-increasing function of its due date. We propose a fast iterative approach to finding a suitable value of the length of the time horizon that needs to be set for the time-indexed formulation and which considerably influences the computation time. Computational results show that the method developed is able to produce optimal, or near-optimal, schedules for real data instances within an acceptable practical time frame.
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