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Evaluation of human-robot order picking systems considering the evolution of object detection
(2022)
The automation of intralogistic processes is a major trend, but order picking, one of the core and most cost-intensive tasks in this field, remains mostly manual due to the flexibility required during picking. Reacting to its hard physical and ergonomic strain, the automation of this process is however highly relevant. Robotic picking system would enable the automation of this process from a technical point of view, but the necessity for the system to evolve in time, due to dynamics of logistic environments, faces operations with new challenges that are hardly treated in literature. This unknown scares potential investors, hindering the application of technically feasible solutions. In this paper, a model for the evaluation of the additional cost of training of automated systems during operations is presented, that also considers the savings enabled by the system after its evolution. The proposed approach, that considers different parameters such as capacity, ergonomics and cost, is validated with a case study and discussed.
The paper focuses on a recently introduced paradigm for the logistic process of picking, with respect to the man-to-goods and goods-to-man concept: the robot to-goods. First the task and system architecture of the fast deployable autonomous commissioning system are described, then the economic efficiency of the system is analysed in a real business case scenario using a simplified method, which is explained and discussed. The clearly positive net present value of the investment and the short payback period obtained in the business case prove how the robot-to-goods paradigm for the commissioning process, implemented through the automation of the forklift platform, is economically attractive for small and medium size enterprises.
Latest advancements in new technologies have made it possible to fully automate the in-plant material flow of small load carriers between the warehouse and the production or assembly line. However, none of methods available in literature fully addresses the planning and dimensioning problem of a logistic system based on these new autonomous technologies. This paper is set to present a method to estimate the fleet size of the new logistic system. After an overview on the state of the art, the method based on combinatorics and probability theory will be explained. A short discussion and suggestions for forthcoming research will conclude the paper.
Powered by e-commerce and vital in the manufacturing industry, intralogistics became an increasingly important and labour-intensive process. In highly standardized automation-friendly environments, such as the automotive sector, most of efficiently automatable intralogistics tasks have already been automated. Due to aging population in EU and ergonomic regulations, the urge to automate intralogistics tasks became consistent also where product and process standardization is lower. That is the case of the production line or cell material supply process, where an increasing number of product variants and individually customized products combined with the necessary ability of reacting to changes in market conditions led to smaller and more frequent replenishment to the points of use in the production plant and to the chaotic addition of production cells in shop floor layout. This led in turn to inevitable traffic growth with unforeseeable related delays and increased level of safety threats and accidents. In this paper, we use the structured approach of the Quality Interaction Function Deployment to analyse the process of supply of assembly lines, seeking the most efficient combination of automation and manual labour, satisfying all stakeholders´ requirements. Results are presented and discussed.
The success of an autonomous robotic system is influenced by several not easily identifiable interdependent factors. This paper is set to lay the foundation of an integrated approach in order to examine all the parameters and understand their contribution to success. After introducing the problem, two autonomous systems for the process of unloading of containers are presented. Then a recently developed method for modelling and interpreting all the parameters, the STIC analysis, are introduced. The preliminary results of applying such a methodology to a first study case is shortly presented. Future research is in the end recommended in order to prove that this methodology is the only way to overcome barriers to the investment in autonomous systems in the logistics sector.
This article discusses the scientifically and industrially important problem of automating the process of unloading goods from standard shipping containers. We outline some of the challenges barring further adoption of robotic solutions to this problem, ranging from handling a vast variety of shapes, sizes, weights, appearances, and packing arrangements of the goods, through hard demands on unloading speed and reliability, to ensuring that fragile goods are not damaged. We propose a modular and reconfigurable software framework in an attempt to efficiently address some of these challenges. We also outline the general framework design and the basic functionality of the core modules developed. We present two instantiations of the software system on two different fully integrated demonstrators: 1) coping with an industrial scenario, i.e., the automated unloading of coffee sacks with an already economically interesting performance; and 2) a scenario used to demonstrate the capabilities of our scientific and technological developments in the context of medium- to long-term prospects of automation in logistics. We performed evaluations that allowed us to summarize several important lessons learned and to identify future directions of research on autonomous robots for the handling of goods in logistics applications.
The appeal of a forklift-free shop floor is pushing enterprises towards lean logistic systems and tugger trains are becoming popular means of supply in intensive material handling production systems. Planning a tugger train system is a complex task influenced by a large set of interrelated parameters. The only standard available to help the planner in designing the tugger train logistic system is the draft norm VDI 5586 (April 2016). However this norm is only applicable under a set of restricting assumptions. In this paper a methodology to complement the approach proposed by the VDI is introduced and then applied to a numerical example. The results are briefly presented and discussed before suggesting forthcoming research.
Planning of available resources considering ergonomics under deterministic highly variable demand
(2020)
In this paper, a method for hybrid short- to long-term planning of available resources for operations is presented, which is based on a known or deterministically forecasted but highly variable demand. The method considers quantitative measures such as the performance and the availability of resources, ergonomically relevant KPI and ultimately process costs in order to serve as a pragmatic planning tool for operations managers in SMEs. Specifically, the method enables exploiting the ergonomic advantages of available flexible automation technology (e.g. AGVs or picking robots), while assuring that these do not represent a capacity bottleneck. After presenting the method along with the necessary assumptions, mainly concerning the availability of data for the calculations, we report a case study that quantifies the impact of throughput variability on the selection of different process alternatives, where different teams of resources are used.
Milk-run systems are becoming more and more popular when it comes to in-plant material supply. Planning and dimensioning such a system poses challenges, which are difficult to overcome, especially in scenarios characterized by a large number of hard constraints and by well-established processes. This paper is set to ease the task of the planner by presenting an innovative flexible method for the planning and dimensioning of in-plant milk-run systems in high constrained scenarios. After an overview on tugger train systems and existing planning methods, an extensive description of the new method will be given. The new method proposed will be critically analyzed and discussed before suggesting forthcoming research.
In standardized sectors such as the automotive, the cost-benefit ratio of automation solutions is high as they contribute to increase capacity, decrease costs and improve product quality. In less standardized application fields, the contribution of automation to improvements in capacity, cost and quality blurs. The automation of complex and unstructured tasks requires sophisticated, expensive and low-performing systems, whose impact on product quality is oftentimes not directly perceived by customers. As a result, the full automation of process chains in the general manufacturing or the logistic sectors is often a sub optimal solution. Taking the distance from the false idea that a process should be either fully automated, or fully manual, this paper presents a novel heuristic method for design of lean human-robot interaction, the Quality Interaction Function Deployment, with the objective of the “right level of automation”. Functions are divided among human and automated agents and several automation scenarios are created and evaluated with respect to their compliance to the requirements of all process´ stakeholders. As a result, synergies among operators (manual tasks) and machines (automated tasks) are improved, thus reducing time-losses and increasing productivity.