Warehouse Construction Research Articles

A Comparative Study on Performance of Conventional and Pre-Engineered Steel Frames Subjected to Crane Load

Abstract: Conventional steel frames are low rise steel frames with roofing systems of truss and roof coverings. Standard hot rolled sections are used for truss elements which are usually much heavier than what is actually required as per the design. Pre– Engineered steel frames are the steel frames in which excess steel is tapered as per the bending moment requirements. In present study, conventional (pratt type) steel roof truss and pre-engineered (portal type) steel roof frame with crane load is considered for an industrial warehouse construction located in Davangere city. 2D Modelling of both conventional and pre-engineered steel frame with crane load is done using STAAD Pro. software. Both the steel frames are subjected to different combinations of Dead load (DL), Live load(LL), Crane Load(CL) and Wind load(WL) as per IS 800 (2007) codal provisions. For the factored bending moments and shear force, referring IS 800 (2007) codal provisions, crane gantry girder is designed as a laterally unsupported member having a combination of I and channel sections. The members of both conventional and pre-engineered steel frames with crane load are designed for the worst load combination as per IS 800(2007) codal provisions. It is concluded that about 25% reduction in quantity of steel can be achieved by choosing pre-engineered steel frame than the conventional steel frame.

Estimating the greenhouse gas emissions of cold chain infrastructure in China from 2021 to 2060

Cold chain infrastructure is vital in the modern food system, yet the greenhouse gas (GHG) emissions of cold warehouse construction and operation are unclear. This article fills the gap by presenting an environmental modeling study to estimate the future trajectory of GHG emissions of cold warehouses in China from 2021 to 2060. A hybrid analysis is used to estimate the potential GHG emissions over time, using environmental input-output analysis (EIO) for construction and process-based analysis for operation. We analyzed five scenarios: cleaner refrigerants (CR), cleaner electricity sources (CE), higher energy efficiency (HE), cleaner cold warehouses (CCW), and a business as usual (BAU) scenario. The results show the trend of GHG emissions in all scenarios and reveal the effectiveness of these measures, with cleaner electricity sources and higher energy efficiency having stronger impacts than introducing cleaner refrigerants on reducing GHG emissions. Another key finding is that electricity consumption during cold warehouse operation is responsible for over 85% of total emissions in 40 years in all scenarios.

GABLE FRAME STRUCTURE PLANNING USING LRFD METHOD IN PAMEKASAN FACTORY WAREHOUSE PROJECT

Currently, the use of steel as a building construction has been widely used as the main material for building structures. Steel frames come in a variety of profiles and sizes. The use of steel frames can be adjusted to the type of construction to be built. From the results of the planning of the WF steel roof structure on the factory warehouse construction project in Pamekasan, it was obtained planning data: Gording using Profile C 125x50x40x4,5. Trekstang uses 8 mm diameter, Wind ties use 10mm diameter steel, Rafter uses WF 350x350x19x19 profile, column uses WF 350x350x19x19 profile, 8 pieces A325 bolts with 22 mm diameter, Hoist Crane Beam uses IWF Bulit-Up beam with 600x1144x18x22 profile, Base Plate uses a size of 500x500x8mm with a column of 600x600.

Road Scene Recognition of Forklift AGV Equipment Based on Deep Learning

The application of scene recognition in intelligent robots to forklift AGV equipment is of great significance in order to improve the automation and intelligence level of distribution centers. At present, using the camera to collect image information to obtain environmental information can break through the limitation of traditional guideway and positioning equipment, and is beneficial to the path planning and system expansion in the later stage of warehouse construction. Taking the forklift AGV equipment in the distribution center as the research object, this paper explores the scene recognition and path planning of forklift AGV equipment based on a deep convolution neural network. On the basis of the characteristics of the warehouse environment, a semantic segmentation network applied to the scene recognition of the warehouse environment is established, and a scene recognition method suitable for the warehouse environment is proposed, so that the equipment can use the deep learning method to learn the environment features and achieve accurate recognition in the large-scale environment, without adding environmental landmarks, which provides an effective convolution neural network model for the scene recognition of forklift AGV equipment in the warehouse environment. The activation function layer of the model is studied by using the activation function with better gradient performance. The results show that the performance of the H-Swish activation function is better than that of the ReLU function in recognition accuracy and computational complexity, and it can save costs as a calculation form of the mobile terminal.

Analysis of clash detection and quantity take-off using BIM for warehouse construction

Lack of integration in the design of a construction project planning, often resulting in clashes between elements. The purpose of this study was to analyze the number and causes of clashes between structural design, precast design, and MEP design for warehousing projects. Then the quantity take-off analysis will be carried out after resolving the clashes. In this study, BIM-based software was used namely Revit® 2020 and Navisworks® Manage 2020. The results of this study found that the number of clashes for the Structural vs Precast components was 289 clashes, for Structural vs MEP components was 191 clashes, and for Precast vs MEP components was 42 clashes. The cause of clashes with the highest percentage was caused by design error (52.36%), followed by design inconsistency (39.13%), and the last was a design discrepancy (8.51%). Based on the calculation of cost changes, a potential saving can be made for HCS panel material and for ducting pipe material as much as 10% of the initial cost.

Earned Value Analysis on National Salt Warehouse Construction Project

Earned Value Analysis is one of the tools used in managing projects that integrate time and cost. The purpose of this study is to calculate Earned Value Analysis using a visual basic program on the time and cost of implementing the National Salt Warehouse construction project, and to get the cause of the delay in the implementation of the National Salt Warehouse construction project. From the results of the calculation of Earned Value Analysis using a visual basic program, (1) North Aceh National Salt Warehouse, in the first week, I experienced a delay of 7 days with a loss of Rp. 980,884 and in the second week finished on schedule, but suffered a loss of Rp. 251,380; (2) Indramayu National Salt Warehouse, in the first week experienced a delay of 5 days with a loss of Rp. 1,999,489 and in the second week experienced a delay of 1 day with a loss of Rp. 1,168,999; (3) Demak National Salt Warehouse, in the first week experienced a delay of 3 days, but experienced a profit of Rp. 1,036,163 and in the second week finished on schedule with a profit of Rp. 9,916,102; (4) Jepara National Salt Warehouse, in the first week experienced a delay of 6 days with a loss of Rp. 202,965 and in the second week experienced a delay of 2 days, but experienced a profit of Rp. 277,461; (5) Pati National Salt Warehouse, in the first week experienced a delay of 6 days with a loss of Rp. 1,167,771 and in the second week finished on schedule, but suffered a loss of Rp. 847,378; (6) Pamekasan National Salt Warehouse, in the first week experienced a delay of 4 days with a loss of Rp. 395,200 and in the second week finished on schedule, but suffered a loss of Rp. 408,000. The causes of the delay in the implementation of the National Salt Warehouse construction project include: (1) the occurrence of unexpected things such as storm floods, earthquakes, landslides, fires, bad weather; (2) improper / wrong construction methods / implementation techniques; (3) identification, duration, and work order plan that is incomplete and not well organized; (4) the owner’s payment system to the contractor that is not in accordance with the contract, (5) the way of inspecting / controlling bureaucratic work by the owner, (6) work accidents that occur to workers.

Influencing Factors Analysis of Ammunition Storage in Reef Environment and Countermeasures

To explore the characteristics of ammunition storage environment in islands of West China Sea and South China Sea and the mechanism of environmental factors affecting ammunition quality change and propose countermeasures, the characteristics of high temperature and humidity, high salt spray and ammunition storage in the sand islands and reefs in southwest China were analysed. During the process of ammunition storage in the west and south China sea islands environment, its quality is affected by many complex factors, among which temperature, humidity and salt fog are the most important factors that result in the change of ammunition quality. For the environment characteristic and the actual situation of the reef storage, some measures are put forward by increasing environmental monitoring equipment and accurately recording the environment parameter, improving the ammunition storage surrounding natural environment, strengthening warehouse construction to improve the heat insulation and moisture proof ability, and strictly implementing the storage environment inspection. The countermeasures proposed can effectively improve the quality of ammunition storage, prolong the life of ammunition and ensure the reliability of ammunition.

Data System Configuration and Organizing and Management Technologies of Information System

Based upon the synopsis of data system and information system, this paper puts forward the data system configuration of information system and execution process of data organizing and management, and sets forth a series of related technologies, such as data warehouse construction technology, data governance technology, data training and learning technology, data syncretization and analysis technology, and data subscription and distribution technology, and moreover, the effectiveness analysis is carried out with a performance comparison between the prototype and the existed system of data organizing and management. This will benefit the further evolution of information system and the continual improvement of data engineering.

Data in Data Warehouse and its Qualities Issues

Data quality (DQ) is as old as the data is. In last few years it is found that DQ can’t be ignored during the process of data warehouse (DW) construction and utilization as it is the major and critical issue for knowledge experts, workers and decision makers who test and query the data for organizational trust and customer satisfaction. Low data quality will lead to high costs, loss in the supply chain and degrade customer relationship management. Hence to ensure the quality before using the data in DW, CRM (Customer Relationship Management), ERP (Enterprise Resource Planning)or business analytics application, it needs to be analyzed and cleansed. In this, we are going to find out the problem regarding dirty data and try to solve them.

Linking Context to Data Warehouse Design

Data warehouses are now widely used for analysis and decision support purposes. The availability of software solutions, which are more and more user-friendly and easy to manipulate has made it possible to extend their use to end users who are not specialists in the field of business intelligence. The purpose of this article is to provide an approach that assists non-expert users in the data warehouse design process and integrates their contextual data. As well as to provide a method that assists non-expert users in data warehouse design process while incorporating their contextual data. Our proposal consists of a context model and a comprehensive Data Warehouse construction method that attaches the context to data warehouses and uses it to produce customized data marts adapted to the decision makers context.

Drilling Material Data Warehouse ETL System Research Based on Crowd-Sourcing

Drilling material data warehouse is an important platform for assisting drilling engineering decision support and data analysis. The construction of high-efficiency and high-quality enterprise-level data warehouse puts high requirements on data quality. The operation targets of oil and gas drilling engineering are buried underground, and there are difficulties in data obtaining. This causes many uncertain data in the oil and gas drilling business database. At the same time, the business database in one area is quite different from those of other areas due to geographical environmental impacts ,so the database selection and integration strategy is uncertain . In order to solve these uncertain problem, this paper proposes building a drilling materials data warehouse ETL system based on crowd-sourcing, and improve the data quality of the data warehouse, thereby improving the efficiency of data warehouse construction.

Combining a continuous location model and Heuristic techniques to determine oilfield warehouse locations under future oil well location uncertainty

A rational decision regarding warehouse location can save logistics costs and improve oilfield operating efficiency. In existing research on oilfield warehouse location problems, it is usually assumed that the oil well locations are known. However, in real oilfield, operations, as well locations, are affected by underground reservoir conditions and the long-term plans of the oilfield company; future well locations that might be serviced by a warehouse are highly uncertain. In addition, previous warehouse location research has tended to solve location problems using a discrete or continuous location model without considering delivery problems. With these deficits in mind, this paper applies a Monte Carlo simulation to simulate future well locations, then selects several suitable candidates using a continuous location model and finally uses discrete location optimization to determine the optimal solution while also considering the distribution interruption problem. Finally, an oil warehouse location problem in the south of the Ordos Basin in China is given as an example of the process. Using relevant data such as number of wells, well locations and materials quantities required, Zhengning is identified as the optimal location for the storage warehouse construction. The simulation indicated that RMB 55,000 would be saved every year, proving the strength of the model to save logistics costs. In an environment in which well locations are uncertain, the combination of a continuous location model and a discrete location model can significantly enhance warehouse location logistics decisions in the oil and gas industries.

Building a Data Store with the Dynamic Structure

This article presents the analysis of approaches to data warehouse construction based on relational and NoSQL solutions and lists the limitations of the relational approach to data mining. The contradiction between data presentation in the real subject domain and the model of data presentation in the relational and NoSQL approaches is revealed. The revealed contradiction is related to the temporality of the values of individual data attributes, the variability of the composition of these attributes, and structure of connections between them. A new logical model of the data warehouse with dynamic structure is proposed. The model is based on the concept of the object as a container for properties storage. Each property of the object includes the property name and two property values without reference and with reference, that are relevant at a given time. The reference property value points to an object whose name is interpreted as the value of the property at a given time. A formal description of the model with allocation of the necessary functionality to manipulate objects and their properties (selectors, predicates, constructors) is given and the necessary control structures are introduced. Substantiation of the proposed model, called an OP-model is given on the basis of compliance with the logical ER data model. It is proved that any ER data model can be implemented in the OP-model. At the same time, the advantages of the OP-model are indicated, they are associated with the possibility of changing connections between entities due to changes in the reference value at a particular time. The potential for scalability of data warehouse due to the unique identification of each object is noted.

A multiproduct single machine economic production quantity model for an imperfect production system under warehouse construction cost

This paper develops an economic production quantity (EPQ) inventory model for a multiproduct single-machine lot-sizing problem with nonconforming items including scrap and rework, where reworks are classified into several groups based on failure severity. In this inventory model, shortage is allowed and is backordered. The aim is to determine the optimal period length, the lot size, and the allowable shortage of each product so as the total cost, including setup, production, warehouse construction, holding, shortage, reworking, and disposal is minimized. Besides, the available total budget is scarce and that there is a lower bound on the service level of each product. While the convexity is proved, an exact method is proposed to solve the nonlinear programming problem. A numerical example is provided at the end to demonstrate the applicability of the proposed solution procedure as well as to perform a sensitivity analysis.

Seismic Behavior of Connections Subjected to Punching Shear in Flat-Slab Systems

Flat-slab structural systems have a large applicability due to their functional and economic advantages. Initially, the reinforced concrete flat slabs had drops and columns with capitals and were considered to be the structures of choice for warehouse construction and heavy loads because shear was not a problem. Flat plates were subsequently developed, with no drops and no column capitals and due to cheaper formwork required, they were popular for residential and office buildings. Flat plate slabs exhibit higher stress at the column connection and are most likely to fail due to punching shear rather than flexural failure. To avoid shear failure, parameters influencing the punching strength need to be clearly investigated by realistic analytical or experimental studies. The present analytical study investigates the influence of some of the parameters governing the behavior of connections under punching shear, which are concrete strength, column aspect ratio, slab thickness and gravity loading. Computer program Structural Analysis Program 2000 V14 is used to model columns and slabs as frame and shell elements, respectively. Parametric studies on aspect ratio and depth-to-span ratio have been carried out using displacement control non-linear static pushover analysis to investigate the influence of these parameters on punching shear capacity of the intermediate and corner column connections, which proved to be the governing criteria to prescribe drift limits for flat plate systems in seismic zones.

Protecting privacy in a clinical data warehouse.

Peking University has several prestigious teaching hospitals in China. To make secondary use of massive medical data for research purposes, construction of a clinical data warehouse is imperative in Peking University. However, a big concern for clinical data warehouse construction is how to protect patient privacy. In this project, we propose to use a combination of symmetric block ciphers, asymmetric ciphers, and cryptographic hashing algorithms to protect patient privacy information. The novelty of our privacy protection approach lies in message-level data encryption, the key caching system, and the cryptographic key management system. The proposed privacy protection approach is scalable to clinical data warehouse construction with any size of medical data. With the composite privacy protection approach, the clinical data warehouse can be secure enough to keep the confidential data from leaking to the outside world.

Study on resources and environmental data integration towards data warehouse construction covering trans-boundary area of China, Russia and Mongolia

The trans-boundary area between Northern China, Mongolia and eastern Siberia of Russia is a continuous geographical area located in north eastern Asia. Many common issues in this region need to be addressed based on a uniform resources and environmental data warehouse. Based on the practice of joint scientific expedition, the paper presented a data integration solution including 3 steps, i.e., data collection standards and specifications making, data reorganization and process, data warehouse design and development. A series of data collection standards and specifications were drawn up firstly covering more than 10 domains. According to the uniform standard, 20 resources and environmental survey databases in regional scale, and 11 in-situ observation databases were reorganized and integrated. North East Asia Resources and Environmental Data Warehouse was designed, which included 4 layers, i.e., resources layer, core business logic layer, internet interoperation layer, and web portal layer. The data warehouse prototype was developed and deployed initially. All the integrated data in this area can be accessed online.

The rise of mega distribution centers and the impact on logistical uncertainty

Between 1998 and 2005, employment in the U.S. warehousing industry grew at a compound annual growth rate of 22.23%, and the number of establishments increased at compound annual growth rate of 9.48%. Over this same period of time, the price for transportation fuels increased dramatically and became much more volatile. In this paper we examine the microeconomic and macroeconomic forces that have enabled such rapid growth in the warehousing industry. We also analyze structural change through employment and warehouse construction starts data and show that a new breed of warehouse has emerged - the mega distribution center, or mega DC. Mega DCs serve mega markets, which allows them to gain advantage through economies of scale and by employing push-pull supply chain strategies that decrease the uncertainty associated with forecasting market demand. Our geographical analyses suggest that this new breed of mega DC is attracted to locations that optimize access to multiple regional markets (and possibly national markets) at the expense of optimizing access to any single market. On average the length of the final leg of the supply chain becomes longer. Because the last leg must be made by truck — which is the least fuel-efficient mode of transport by far — the location requirements of this new breed of mega DC increase supply chain exposure to the related risks of rising and increasingly volatile fuel prices.

From conceptual models to schemata: An object-process-based data warehouse construction method

Data warehouse modeling is a complex task, which involves knowledge of business processes of the domain of discourse, understanding the structural and behavioral system's conceptual model, and familiarity with data warehouse technologies. The suitability of current data warehouse modeling methods for large-scale systems is questionable, as they require multiple manual actions to discover measures and relevant dimensional entities and they tend to disregard the system's dynamic aspects. We present an Object-process-based Data Warehouse Construction (ODWC) method that overcomes these limitations of existing methods by utilizing the operational system conceptual model to construct a corresponding data warehouse schema. We specify the ODWC method, apply it on a case study, evaluate it, and compare it to existing methods.

Web warehouse – a new web information fusion tool for web mining

In this study, we introduce a web information fusion tool – web warehouse, which is suitable for web mining and knowledge discovery. To formulate a web warehouse, a four-layer web warehouse architecture for decision support is firstly proposed. According to the layered web warehouse framework architecture, an extraction–fusion–mapping–loading (EFML) process model for web warehouse construction is then constructed. In the web warehouse process model, a series of web services including wrapper service, mediation service, ontology service and mapping service are used. Particularly, two kinds of mediators are introduced to fuse the heterogeneous web information. Finally, a simple case study is presented to illustrate the construction process of web warehouse.