Efficient Material Handling System Research Articles

Generation of material handling system alternatives: A constraints satisfaction problem approach

In the context of Industry 4.0, the design of efficient Material Handling Systems (MHS) plays a critical role in optimizing industrial operations and enhancing productivity. The integration of advanced technologies, automation, and complex systems has revolutionized industrial processes, emphasizing the need for defining coherent MHS alternatives prior to the deployment of a specific solution. This paper presents an integrated MHS alternative generation approach that combines MHE allocation, fleet sizing, and key performance indicator (KPI)-based evaluation to enhance MHS. The proposed approach deploys a Constraint Satisfaction Problem (CSP) framework, which defines the conditions that must be satisfied by the values assigned to the MHE allocation and fleet sizing variables. The constraints capture the physical and operational characteristics of MHE and MHS, ensuring that the generated alternatives adhere to the specific requirements and limitations of the system. Once a set of feasible MHS alternatives complying with various constraints is established, further assessments can be carried out to gauge the dynamic behavior of these systems using methods like Discrete Event Simulation. The paper emphasizes the importance of incorporating a broader range of data categories, such as layout constraints, product characteristics, and Industry 4.0 challenges, to enhance the effectiveness and accuracy of the MHS design process. To evaluate the generated alternatives, a set of KPIs is proposed, encompassing operational, economic, environmental, safety, and security aspects. These KPIs enable decision-makers to assess alternative performance across multiple metrics, aiding in the identification of relevant solutions aligned with company objectives. The incorporation of KPIs provides a pre-evaluation of MHS alternatives, streamlining subsequent simulation and multicriteria decision-making processes. This research acknowledges the importance of alternative generation as an integral part of the broader MHS design problem.

Simulation-based optimization for material handling systems in manufacturing and distribution industries

Faced with rising customer expectations, shortening product life cycle and increasing number of competitors, many companies are paying increasing attention to streamline their operations with a view to improving the timeliness in response to changes and demands in their supply chains. Material handling is a vital element of the supply chains, which involves a variety of operations including the movement, storage, protection and control of materials and products throughout the processes of manufacturing and distribution. Having efficient material handling systems is of great importance to these industries for maintaining and facilitating a continuous flow of materials through the workplace and guaranteeing that required materials are available when needed. In this paper, we apply a simulation-based optimization framework for solving several real-life single objective and multi-objective optimization problems. The results reveal that the simulation-based optimization framework could become an effective decision making tool for solving both single and multi-objective optimization problems in manufacturing and distribution industries and help management to find near-optimal system parameters to fulfill important objectives.

Material supply scheduling in a ubiquitous manufacturing system

Recently, ubiquitous manufacturing has attracted wide attention in both academia and industry. To create a successful ubiquitous manufacturing system, an efficient material handling system is essential. In accordance with this reason, mobile robots have been used for transporting materials. This paper aims at developing a methodology for scheduling the material supply for a single mobile robot in a ubiquitous manufacturing environment. In this type of environment, the processing rate of the materials along with supply quantity corresponds to the cycle of material supply. The carrying capacity of the robots are limited and thus the problem of determining the material supply quantity and material supply schedule without lack of materials for production or service processes becomes complicated. In this work, a nonlinear program is formulated to schedule the supply of material and determine the required material quantity. A heuristic algorithm based on genetic algorithm is developed to solve the problem. From the numerical experiments conducted in this study, it is observed that the proposed algorithm shows good performance and can also be implemented to solve large scale problems.

Combined Energy and Process Simulation to Foster Efficiency in Non-automated Material Handling System Design

Energy and resource efficiency are becoming more and more important objectives in industrial companies, so that it has also become relevant to material handling as part of the lean strategy in supply chain management. The design of sustainable, energy efficient material handling systems and processes depends on methods and tools that analyse and evaluate the composition of the technologies and processes of the system. Therefore analysis on detailed data on energy consumption, energy supply and process organisation is required to improve overall system efficiency. This study proposes a novel approach to energy data generation based on Standardised Energy Consuming Activities (SECA). Simulating process energy consumption and consumption behaviour based on process function investigations increases knowledge about the sequence and characteristics of energy consumption and its process allocation. Executing the research project Usable Battery Energy of the material handling equipment was identified to be gradable by 25% to 43% in order to increase equipment availability and thus system efficiency. In the performed case study a system range extension of 19% to 33% was reached by the implementation of a fast engaging charging system using process related idle times. Generally applicable data is required for the design of a scalable simulation to enable the identification of requirements to the design of non-automated material handling system components. The proposed framework forms the basis necessary for the derivation and evaluation of technical and organisational improvement of system efficiency with respect to energy, ecological and economic objectives.

A New Grain Harvesting System for Single-Pass Grain Harvest, Biomass Collection, Crop Residue Sizing, and Grain Segregation

A cereal grain harvesting system is introduced that combines existing technologies in a unique way to improve cereal grain harvest performance, increase profitability, and efficiently collect biomass. The harvesting system is comprised of three machines: one to reap grain, harvest biomass, and size crop residue for no-till seeding; a second to thresh and winnow the grain; and a third to separate the grain by quality for added value. This study describes the new harvesting system and the development of one of the system's major components: the reaper/flail harvester. The reaper/flail harvester consists of a mobile power unit, a stripper header to harvest the crop, and a flail to chop the standing residue into small pieces. A prototype harvester was fabricated and tested to determine system design criteria and performance characteristics in terms of machine power requirements, quantity of biomass collected, and bulk density of the material harvested. Trials were conducted in seven wheat (Triticum aestivum L.) fields in Oregon during 2005 and 2006 that ranged in yield from 3.3 to 6.4 t ha-1. Harvester performance was evaluated at various travel speeds, straw chop heights, and with different types of wheat. Flail power requirements were highly linearly correlated with quantity and rate of biomass chopped (R2 = 0.91). The maximum reaping power requirement was 2.7 kW m-1, only slightly higher than the no-load power requirement of 1.9 kW m-1. Power requirements for reaping, conveying, and flailing ranged from a low of 5.0 to a high of 13.5 kW m-1 depending on travel speed, crop yield, biomass concentration, and chop height. Values were linearly correlated with the combined grain, chaff, and biomass feed rate (t h-1) with an R2 of 0.88. Total machine power requirements for a harvester with a 7.3 m header would be about 175 kW, including 75 kW for propulsion, losses, and reserve. Chaff yield in the grain/chaff (graff) mixture harvested exceeded 2 t ha-1 in six of the seven trials. With chaff valued at $23 t-1, collecting 2 t ha-1 of chaff would increase farm revenues by $46 ha-1. Realistic graff densities of awned wheat were less than 1/11 that of clean grain, and new, efficient material handling systems would need to be developed to have harvesting capacities comparable to that of a conventional combine-based system. Awnless wheat had graff densities that averaged about 1/5 that of clean grain. Equipment is commercially available to handle this volume of material and have harvesting field capacities comparable to that of a conventional combine-based system.