A Planning Approach for In-plant Milk Run Processes to Optimize Material Provision in Assembly Systems

Droste, Markus; Deuse, Jochen

doi:10.1007/978-3-642-23860-4_99

Cited by 20 publications

(7 citation statements)

References 9 publications

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“…Usually areas beside stations are scarce and not enough to hold a lot of inventory. Another strategy in which assembly workers can get parts in small bins very close to them is milk run system in which a group of stations is fed by the same tugger or tow train in the same route where each station gets its demand of parts for a certain period (Droste & Deuse 2011). …”

Section: Introductionmentioning

confidence: 99%

Efficient material flow in mixed model assembly lines

Alnahhal

Noche

2013

SpringerPlus

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In this study, material flow from decentralized supermarkets to stations in mixed model assembly lines using tow (tugger) trains is investigated. Train routing, scheduling, and loading problems are investigated in parallel to minimize the number of trains, variability in loading and in routes lengths, and line-side inventory holding costs. The general framework for solving these problems in parallel contains analytical equations, Dynamic Programming (DP), and Mixed Integer Programming (MIP). Matlab in conjunction with LP-solve software was used to formulate the problem. An example was presented to explain the idea. Results which were obtained in very short CPU time showed the effect of using time buffer among routes on the feasible space and on the optimal solution. Results also showed the effect of the objective, concerning reducing the variability in loading, on the results of routing, scheduling, and loading. Moreover, results showed the importance of considering the maximum line-side inventory beside the capacity of the train in the same time in finding the optimal solution.

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Section: Introductionmentioning

confidence: 99%

Efficient material flow in mixed model assembly lines

Alnahhal

Noche

2013

SpringerPlus

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“…Faccio et al (2013a) suggested a method for determining the optimal number of kanbans in supermarkets, while Faccio et al (2013b) developed a general framework to design and simulate supermarket and milk run-based component feeding systems. Kilic et al (2012) classified milk runs distribution systems, while Droste and Deuse (2011) and Alnahhal and Noche (2013) developed models for milk runs planning. Satoglu and Sahin (2013) developed a mathematical model and heuristic method to design milk run systems in order to feed assembly line just in time minimizing inventory and material handling costs.…”

Section: Literature Reviewmentioning

confidence: 99%

Planning models for continuous supply of parts in assembly systems

Caputo

Pelagagge

Salini

2015

Assembly Automation

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Access to this document was granted through an Emerald subscription provided by 331053 [] For AuthorsIf you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation.

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“…The manufacturing industry is faced with both rare opportunities and enormous challenges. With the continuous improvement of living standards, the customers have been raising increasingly diverse, subjective and individualized demands for products [2], while the emergence of new techniques have greatly accelerated the renewal of products. Overall, the traditional mass production is shifting towards modern production modes like lean production [3].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Multi-Task Job-Shop Scheduling Based on Uncertainty Theory Algorithm

Chen¹,

Deng²,

Wang³

2018

Int. j. simul. model.

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This paper aims to solve the difficulties in job-shop scheduling, a key determinant of production cost and economic effectiveness of manufacturing enterprises. For this purpose, the existing job-shop scheduling problems were introduced, the internal and external uncertainties that may influence the scheduling plan in actual production were enumerated, and the corresponding scheduling and rescheduling strategies were reviewed one by one. Then, the flexible job-shop model was established under uncertainties, the mathematical models were created considering such three uncertainties as the discrete makespan, rush order cut-in and machine failure, and the proactive-reactive scheduling strategy was proposed against emergencies or uncertainties. Finally, the proactive-reactive scheduling strategy, developed based on the uncertainty theory, was proved effective and feasible through the simulation experiments on scheduling optimization under machine failure and rush order cut-in. The research findings shed new light on the production planning and scheduling strategy of manufacturing enterprises.

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A Planning Approach for In-plant Milk Run Processes to Optimize Material Provision in Assembly Systems

Cited by 20 publications

References 9 publications

Efficient material flow in mixed model assembly lines

Efficient material flow in mixed model assembly lines

Planning models for continuous supply of parts in assembly systems

Optimization of Multi-Task Job-Shop Scheduling Based on Uncertainty Theory Algorithm

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