Carla A. S. Geraldes

A warehouse design decision model — Case study

Todaypsilas competitive and volatile market requires flexibility, quality and efficiency from the logistics operations. In this context, warehouses are an important link of the logistic chain and warehouse management plays an important role over customerpsilas service. Throughout this work we analyze a mathematical model aiming to support warehouse management decisions. A case study is used for that purpose and the model jointly identifies product allocation to the functional areas in the warehouse, as well as the size of each area. This case study also evaluates the performance of the model when real data is used. Model is solved using LINGO 9.0 mixed-integer commercial solver, and potential savings achieved using the proposed technique are discussed.

Warehouse design and planning: a mathematical programming approach

The dynamic nature of todays competitive markets compels organizations to an incessant reassessment in an effort to respond to continuous challenges. Therefore, warehouses as an important link in most supply chains, must be continually re-evaluated to ensure that they are consistent with both markets demands and managements strategies. A number of warehouse decision support models have been proposed in the literature but considerable difficulties in applying these models still remain, due to the large amount of information to be processed and to the large number of possible alternatives. In this paper we discuss a mathematical programming model aiming to support some warehouse management and inventory decisions. In particular a large mixed-integer nonlinear programming model (MINLP) is presented to capture the trade-offs among the different inventory and warehouse costs in order to achieve global optimal design satisfying throughput requirements.

Multi-agent System Architecture for Zero Defect Multi-stage Manufacturing

Multi-stage manufacturing, typical in important industrial sectors, is inherently a complex process. The application of the zero defect manufacturing (ZDM) philosophy, together with recent technological advances in cyber-physical systems (CPS), presents significant challenges and opportunities for the implementation of new methodologies towards the continuous system improvement. This paper introduces the main principles of a multi-agent CPS aiming the application of ZDM in multi-stage production systems, which is being developed under the EU H2020 GO0D MAN project. In particular, this paper describes the MAS architecture that allows the distributed data collection and the balancing of the data analysis for monitoring and adaptation among cloud and edge layers, to enable the earlier detection of process and product variability, and the generation of new optimized knowledge by correlating the aggregated data.

An automated warehouse design validation using discrete simulation

In this paper we discuss the use of discrete simulation technique to support the redesign process of an automated warehouse system of the Brazilian Air Force unit. This unit is responsible for the supply of all uniform items and other military support material to their military forces. In particular, our work aims at analysing the inclusion of an automated sorting system to prepare uniforms individual kits in order to release downstream supply chain from this task. The main challenge was to investigate the impact on the existing storage system of a new sorting system and, simultaneously, to explore if additional management measures are required to satisfy both throughput levels and overall supply chain requirements. To accomplish a solution for such a complex problem simulation models were developed using ARENA software. Results have shown that the use of simulation allows not only the assessment of the impact of the new sorting equipment but also to test different warehouse management strategies that should be adopted concurrently to ensure that desired throughput levels can be achieved in the new scenario. In fact, this research illustrates the flexibility of the simulation tool to address several complex management issues simultaneously such as the introduction of picking sequencing rules, the use of a class-based storage policy, the addition of new picking stations, and an increase of the number of the available boxes used for transportation.