Dynamic mosaic planning for a robotic bin-packing system based on picked part and target box monitoring

This paper describes the dynamic mosaic planning method developed in the context of the PICKPLACE European project. The dynamic planner has allowed the development of a robotic system capable of packing a wide variety of objects without having to adjust to each reference. The mosaic planning system consists of three modules: First, the picked item monitoring module monitors the grabbed item to find out how the robot has picked it. At the same time, the destination container is monitored online to obtain the actual status of the packaging. To this end, we present a novel heuristic algorithm that, based on the point cloud of the scene, estimates the empty volume inside the container as empty maximal spaces (EMS). Finally, we present the development of the dynamic IK-PAL mosaic planner that allows us to dynamically estimate the optimal packing pose considering both the status of the picked part and the estimated EMSs. The developed method has been successfully integrated in a real robotic picking and packing system and validated with 7 tests of increasing complexity. In these tests, we demonstrate the flexibility of the presented system in handling a wide range of objects in a real dynamic packaging environment. To our knowledge, this is the first time that a complete online picking and packing system is deployed in a real robotic scenario allowing to create mosaics with arbitrary objects and to consider the dynamics of a real robotic packing system.This article has been funded by the European Union's Horizon 2020 research and Innovation Programme under grant agreement No. 780488, and the project "5R-Red Cervera de Tecnologias roboticas en fabricacion inteligente", contract number CER-20211007, under "Centros Tecnologicos de Excelencia Cervera" programme funded by "The Centre for the Development of Industrial Technology (CDTI)"

Progress in Material Handling Research: 2010

Table of Content

Determine planning method in the storage area

ABSTRACT Ji Yuan Hai Wan Shi Ye AB started in the December of 2011, is co-funded by the Xiamen Hai Wan AB and Luo Yang Shi Hua. It has integrated business such as scientific research, production and trade together. The company locates in the industrial manufactory area at Ji Yuan, Henan Province. The main products are verity of unsaturated polyester resin. Their products are widely used in the fields like industry, agricultural, transportation and construction. This shows its wide coverage status quo and broad future (Company´s website). Inventory is the network-node among goods flow, information flow and cash flow, and is of great importance to economic development nowadays. The rational management in transportation, packaging, loading/unloading, processing, delivery, can efficiently alleviate working strength, damage ratio, Inventory turnover and distribution costs. The storage area is not only the most important but also the most difficult part to plan. According to the statistics, unloading, picking, sorting and loading take 40% time of the whole process, and the rest are consumed by staff’s patrolling. As a result, a cost effective design in storage area can effectively lower down internal transportation cost, and highly improve the performance of the whole inventory. In order to increase the efficiency inside storage area, and create a best possible environment for material handlers in the inventory; this article intended to generate a directive description by studying the design inside storage area of the inventory. Based on the case study, author has raised a recommendation to the inventory´s equipment and slot planning. MATLAB is the main programming tool in the slot planning and it contains aspects below: 1, A brief introduction to company and their main activities. 2, Storage area planning and design theories: The definition, types, functions of storage area were introduced in the beginning. Then storage area and several ways of storage were briefly described. At last, author described the classical EIQ analysis and its applications in the logistics system. Page IV 3, Selection of equipment in storage area Author elaborated basic principles of the equipment choice; and introduced types, choice methods in storing and material handling equipment. Finally the EIQ analysis was applied and its influence in equipment choice was proved. 4, Planning and design of slots in the storage area This part mainly included following contents A. Coding The article began with methodology introduction for the coding of both location and goods, and the principles of choice methodology for different goods. B. Spacing plan and corresponding information Principles and concepts of location planning as well as corresponding benefits were introduced, which are the reasons of location planning. C. Modeling The author has presented the aim of the location planning; and according to that, a model has been introduced. There are two things has to be concerned, one is the total transporting distance for the goods and the other one is the stability of the racking. The aim of the location planning is to increase picking efficiency by storing the fastest-moving goods in the most convenient positions which is gate in this case. To increase racking ´s stability, lighter goods have to put in higher than heavier things. D. The algorithm Location planning is a multi-objective optimization problem. Author has analyzed and compared several algorithms; finally genetic algorithm was chosen to solve the problem. Author introduced the principles of the methodology about using genetic algorithm to solve a multi-objective optimization problem. After that, according to the model introduced in the previously step, author has decided to use parallel selection method, multi-Gender evolutionary method and constraint method. To get an optimal solution of location planning, MATLAB has been used as the tool. Page V 5, Applied and analyzed the methods and programs, mentioned in the article, to the design of inventory´s storage area. 6, Summary and prospect Author has summarized the article’s result and raised future research topics. This article has given some new points in the following aspect： 1．By thinking of velocity of goods circulation and goods weigh, a multi-objective optimization model for location planning has been made. Model has been solved, via using Genetic Algorithm’s paratactic selection, multi-gender evolution and constraint methods. 2．By using MATLAB, author programmed the location plan which generates solutions to optimization problems using techniques inspired by natural evolution. Programming has been used crossover, mutation methods and the algorithm terminated when the 500 generations has been produced, then a satisfactory fitness solution has been reached for the location

Volumetric Techniques for Product Routing and Loading Optimisation in Industry 4.0: A Review

Industry 4.0 has become a crucial part in the majority of processes, components, and related modelling, as well as predictive tools that allow a more efficient, automated and sustainable approach to industry. The availability of large quantities of data, and the advances in IoT, AI, and data-driven frameworks, have led to an enhanced data gathering, assessment, and extraction of actionable information, resulting in a better decision-making process. Product picking and its subsequent packing is an important area, and has drawn increasing attention for the research community. However, depending of the context, some of the related approaches tend to be either highly mathematical, or applied to a specific context. This article aims to provide a survey on the main methods, techniques, and frameworks relevant to product packing and to highlight the main properties and features that should be further investigated to ensure a more efficient and optimised approach

Improving warehouse responsiveness by job priority management: a European distribution centre field study

Warehouses employ order cut-off times to ensure sufficient time for fulfilment. To satisfy increasing consumer’s expectations for higher order responsiveness, warehouses competitively postpone these cut-off times upholding the same pick-up time. This paper, therefore, aims to schedule jobs more efficiently to meet compressed response times. Secondly, this paper provides a data-driven decision-making methodology to guarantee the right implementation by the practitioners. Priority-based job scheduling using flow-shop models has been used mainly for manufacturing systems but can be ingeniously applied for warehouse job scheduling to accommodate tighter cut-off times. To assist warehouse managers in decision making for the practical value of these models, this study presents a computer simulation approach to decide which priority rule performs best under which circumstances. The application of stochastic simulation models for uncertain real-life operational environments contributes to the previous literature on deterministic models for theoretical environments. The performance of each rule is evaluated in terms of a joint cost criterion that integrates the objectives of low earliness, low tardiness, low labour idleness, and low work-in-process stocks. The simulation outcomes provide several findings about the strategic views for improving responsiveness. In particular, the critical ratio rule using the real-time queue status of jobs has the fastest flow-time and performs best for warehouse scenarios with expensive products and high labour costs. The case study limits the coverage of the findings, but it still closes the existent gap regarding data-driven decision-making methodology for practitioners of supply chains

The Prediction of Optimal Route of City Transportation Based on Passenger Occupancy using Genetic Algorithm: A Case Study in The City of Bandung

Currently, the existence of city transport is increasingly eliminated by private vehicles such as cars and motorcycles. This situation is further exacerbated by the behavior of city transport drivers who are less discipline in driving, or in picking up and dropping off their passengers. The bad behavior is partly caused by the low level of passenger occupancy. The drivers try to search for passengers as much as possible but often ignore the traffic rules. To overcome this problem, an optimal transport route with high passenger potential is required. Therefore, this study investigated the optimal route of city transport based on the passenger occupancy rate in the city of Bandung as the case study. The method employed for determining the optimal route is Genetic algorithm combined with Ordinary Kriging method used for the process of passenger prediction and fitness calculation. The optimal routes are those with higher occupancy rate. The analysis results showed that the use of the Genetic algorithm with a low number of generations succeed in creating new optimal routes even though the increase is not too high the maximum only reaches 4%.This result is certainly important enough to be used in making better public transport routes