• Journal of Construction Engineering and Project Management
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• v.6 no.1
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• pp.11-19
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• 2016

Most of the Indian contractors are not well equipped to handle the growing demand of infrastructure development; hence construction projects frequently run in to time and cost overruns, disputes and quality issues. This study aims to improve the construction industry in India by implementing lean principles to eliminate non-value adding activities (wastes). The purpose of this study is to 1) identify the wastes and their sources affecting the construction process, and 2) to identify problems and document lessons by applying a Last Planner System (LPS) to a sample project. First, the researchers identified that Delays, Rework, and Interruptions were the most critical wastes affecting the construction process and Poor management control, Poor Planning and Shortage of Resources were the major sources of the above mentioned wastes. Second, the researchers report the Percent of Planned Complete (PPC) analysis results and experienced problems after implementation of LPS at the sample project. It was observed that much more improvement could have been achieved if there was consensus between the owners and the contractor on the implementation of the LPS in its entirety. Some of the problems experienced in the implementation of the LPS like lack of scheduling, resource and material shortage were found to be similar to those in developed countries.

• Korean Journal of Construction Engineering and Management
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• v.8 no.4
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• pp.119-127
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• 2007

Cost and Schedule is the most important information, and how efficiently manage this information is the key issue for Construction Project Management. Domestically, systematic scheduling method such as CPM network is not only used widely but integration of time and cost information also is. In order to effectively integrate and use the time and cost information, it is suggested that WBS(Work Breakdown Structure) based QDB(Quantity Database) should be generated from the design phase and, WBS and QDB related system tool should be supported. It could be helpful to relate and integrate other construction project information.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.1
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• pp.21-28
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• 2013

The paper proposes an optimal sizing method of a customer's battery energy storage system (BESS) which aims at managing the electricity demand of the customer to minimize electricity cost under the time of use(TOU) pricing. Peak load limit of the customer and charging and discharging schedules of the BESS are optimized on annual basis to minimize annual electricity cost, which consists of peak load related basic cost and actual usage cost. The optimal scheduling is used to assess the maximum cost savings for all sets of candidate capacities of BESS. An optimal size of BESS is determined from the cost saving curves via capacity of BESS. Case study uses real data from an apartment-type factory customer and shows how the proposed method can be employed to optimally design the size of BESS for customer demand management.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.304-308
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• 2009

This paper presents the deadline driven CPU-Power management scheme for the Real-Time Embedded OS: named TMO-eCos. It used the scheduling scenarios generated by a task serialization technique for hard real- time TMO system. The serializer does a off-line analysis at design time with period, deadline and WCET of periodic tasks. Finally, TMO-eCos kernel controls the CPU speed to save the power consumption under the condition that periodic tasks do not violate deadlines. As a result, the system shows a reasonable amount of power saving. This paper presents all of these processes and test results.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.686-693
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• 2022

Construction is a collaborative endeavor. The complexity in delivering construction projects successfully is impacted by the effective collaboration needs of a multitude of stakeholders throughout the project life-cycle. Technologies such as Building Information Modelling and relational project delivery approaches such as Alliancing and Integrated Project Delivery have developed to address this conundrum. However, with the onset of the pandemic, the digital economy has surged world-wide and advances in technology such as in the areas of machine learning (ML) and Artificial Intelligence (AI) have grown deep roots across specializations and domains to the point of matching its capabilities to the human mind. Several recent studies have both explored the role of AI in the construction process and highlighted its benefits. In contrast, literature in the organization studies field has highlighted the fear that tasks currently done by humans will be done by AI in future. Motivated by these insights and with the understanding that construction is a labour intensive sector where knowledge is both fragmented and predominantly tacit in nature, this paper explores the integration of AI in construction processes across project phases from planning, scheduling, execution and maintenance operations using literary evidence and experiential insights. The findings show that AI can complement human skills rather than provide a substitute for them. This preliminary study is expected to be a stepping stone for further research and implementation in practice.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.459-466
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• 2013

Risk exists in all construction projects and resides among the collection of subcontractors and their array of individual activities. Wherever risk resides, the interrelation of participants to one another becomes paramount for the way in which risk is measured. Inherent risk becomes recognizable and quantifiable within network schedules in the form of consuming float - the flexibility to absorb delays. Allocating, owning, valuing, and expending such float in network schedules has been debated since the inception of the critical path method itself. This research investigates the foundational element of a three-part approach that examines how float can be traded as a commodity, a concept whose promise remains unfulfilled for lack of a holistic approach. The Capital Asset Pricing Model (CAPM) of financial portfolio theory, which describes the relationship between risk and expected return of individual stocks, is explored as an analogy to quantify the inherent risk of the participants in construction projects. The inherent relationship between them and their impact on overall schedule performance, defined as schedule risk -the likelihood of failing to meet schedule plans and the effect of such failure, is matched with the use of CAPM's beta component - the risk correlation measure of an individual stock to that of the entire market - to determine parallels with respect to the inner workings and risks represented by each entity or activity within a schedule. This correlation is the initial theoretical extension that is required to identify where risk resides within construction projects, allocate and commoditize it, and achieve actual tradability.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.223-224
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• 2023

Optimal fleet management in the planning stage is one of the most critical activities that guarantee successful construction projects. In South Korea, the construction standard production rate database (CSPRD) is normally employed. However, when it comes to a trade-off problem that involves decision-making on optimal sets of equipment to perform a certain task, the method will require the planners' in-depth knowledge and experience regarding the target process and a time consuming estimation of the performance of every possible scenario must be conducted for the deduction of the optimal fleet management. On this account, this research paper proposes a lightweight method of using mixed integer nonlinear programming (MINLP) in multi-objective problems based on CSPRD-based mathematical equations to assist planners in the preplanning stage of choosing the optimal sets of types and size machinery to efficiently arrange the construction scheduling and budgeting.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.598-601
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• 2003

As the scale of construction work is enlarged, complicated and diversified, construction information from the large number of construction sites is happened and reported to the head office. To control much information generated in construction sites simultaneously, the necessity of supporting system which can extract necessary information is increased. However, compare with large companies, medium-sized companies's organization of head office and management system is weak, so it's difficult to manage multi-projects. Among these site managements, resource management is an important management area. But, resource planning is based on experience and judgement and have not associated with schedule information. So when schedule if changed, the plan must be amended manually. This study investigates material-planning model for multi-project management which is connected with daily report system and scheduling software.

• The Journal of Information Systems
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• v.12 no.2
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• pp.129-149
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• 2003

One of the important applications in Enterprise Resource Planning(ERP) systems is the Manufacturing Resource Planning(MRPII) system using Bill of Material(BOM). The manufacturing resource planning determines the quantity and timing of the production or purchase of subassemblies and raw materials needed to support the Master Production Scheduling(MPS). The bill of material is the recipe, a list of the materials needed to make a product. This paper intends to suggest a component-based materials management system using Unified Modeling Language(UML), as an application system for automobile part industry. Applying component based materials management systems designed with UML methodology, we analyzed the workflow and the document on materials management process from production planning to inventory management, and implemented a prototype of efficient materials management system, as a surrogate of existing material requirement planning(MRPI) system. To produce many other assemblies for a automobile part firm, component parts are assembled into subassemblies that are joined to assemble the finished product. Through the system suggested in this study, the level of inventory has cut down and the cost of inventory management has decreased. Also, the development method using UML makes the analysis and design phase to shorten in implementation period of MRPII system. The implementation of materials management system using CBD shows the ease of use in software reuse and the interoperability with corporate Internal information system. The result of applying object-oriented CBD technique is to minimize the risk of life cycle and facilitate the reuse of software as mentioned to limitation of information engineering methodology.