Planned Completion Time Research Articles

Analisis Keterlambatan Proyek PT. PP Persero Tbk Pada Pembangunan Gedung MRT Dengan Menggunakan Lean Six Sigma Framework

In general, each construction project has a planned completion time with a set scheduling so that the project can run well. Indonesia is trying to develop infrastructure and public facilities such as the MRT Building Construction Project. This research was conducted at the MRT HUB Building Construction Project Simpang Temu Dukuh Atas Jalan Kendal No. 25, Menteng, Central Jakarta, Special Capital Region of Jakarta 10310 at PT. PP (Persero), Tbk This research aims to obtain factors that cause project delays. This research uses the concept of lean six sigma with the DMAIC phase (Define, Measure, Analyze, Improve, and Control). After being identified, the construction experienced delays in work completion caused by several factors such as overpurchase, delay, and inventories. Lean six sigma helps in finding solutions to minimize delays including not buying goods excessively so as not to cause delays so that workers can work properly without having to wait for the area to be worked on.

바람직한 이유식 실천 방향 모색을 위한 영유아의 식생활 현황 조사

Purpose: This study was conducted to investigate the status of baby foods and baby food preferences in Korea in the late 2010s. Methods: The subjects were 410 mothers with 6-18-month-old infants. A questionnaire was developed based on a literature review and consisted of items related to baby food, the food preference of babies, and the eating habits of the mothers and babies. An online survey was conducted for 5 days in July 2018. Results: The majority of the respondents began weaning when the baby was 5 months old (46.8%), and the completion or planned completion time of weaning was between 12 and 15 months (61.0%). More than half of the mothers (62.2%) prepared baby foods from scratch at home instead of feeding babies commercial baby foods. Among the 41 food items surveyed, rice porridge was the most used baby food (96.8%) followed by beef (93.4%) and apple (90.5%) while the least used baby foods were drinks (8.5%), which reflected the introduction of these foods during weaning. Babies preferred snacks (4.36) the most, followed by cheese (4.35), liquid yogurt (4.27) and strawberries (4.27). The least liked baby foods were drinks (2.51), shellfish (2.96), and nuts (3.06). The mothers’ diets were more irregular (45.6%) or unbalanced (46.6%) than their babies (both 5.4%). Conclusion: Problems in a mother''s diet could affect her baby’s dietary habits. Therefore, practical nutrition education and counseling on a proper diet, as well as on how to provide baby food, should be conducted so that mothers can maintain a desirable attitude toward their own diet and baby foods.

Energy optimization of the configurable service portfolio for IoT systems

The development of the Internet of Things technology has promoted the continuous improvement of information technology in various fields such as industry, military and transportation. And communication and information exchange through the Internet, with the ability to sense, so smart devices came into being. First, this article proposes an IoT service framework that encapsulates each function of a smart device in an IoT environment into a service that is aggregated into a service class based on the similarity of its functions. Secondly, based on the particle swarm optimization algorithm, the correct service combination is recommended for the service chain. The gray correlation degree evaluation method is used to serve configurable resources, and the combined energy scheme is used for multi-objective comprehensive evaluation. Among them, the configurable service combination plan is evaluated from four aspects: service resource cost, planned completion time, overdue time and resource idle rate. The experimental results show that the particle swarm optimization algorithm can obtain a relatively good IoT service combination, which has better performance than genetic algorithms and ant colony algorithms, and can maintain the load balance of smart devices in load balancing, thereby effectively extending the entire network Life cycle.

Minimizing Earliness/Tardiness costs on multiple machines with an application to surgery scheduling

Early or tardy surgeries are frustrating for both patients and personnel, and cause inefficient use of resources at the operating rooms. The stochastic Earliness/Tardiness (E/T) scheduling problem addresses this by minimizing the total expected deviation of the surgery completion times from the planned completion times. We introduce the concept of E/T-concavity as a property of a probability distribution if the E/T costs are concave as a function of the standard deviation of the completion time, whenever the optimal planned completion times are selected. We use this concept to generate an optimal schedule for the multiple machine variant of the E/T problem. The optimal schedule is not unique and therefore allows us to consider several optimization objectives in addition to the E/T objective. We demonstrate the usefulness of our results in practice by proving E/T-concavity for several probability distributions and by showing that, under the assumption of E/T-concavity, a simple Shortest Variance First (SVF) rule is optimal. We conclude by providing a numerical example of surgery scheduling where we demonstrate the benefits of the SVF rule compared to several commonly used scheduling rules.

Supply Chain Management of Road Projects in India using FMEA and ISM Technique

Objective of the Study: This paper aims to study about the risks that affect the supply chain management of the road infrastructure projects. Supply chain management identifies the issues that slow down the process of road construction and helps in reconfiguration and re-engineering of supply chain. Methodology: A thorough literature review has been conducted to identify the major factors that cause delay in the completion of the road projects. After analysis of reviewed literature a questionnaire survey was prepared. The gathered data was analyzed and top ten risk factors having highest Risk Priority Number (RPN) were identified from Failure Mode and Effect Analysis technique (FMEA). The relationship between the various risks factors has been identified by the interpretive structural modeling (ISM). Findings: The findings of the study indicate that there are several risks that create a gap between planned completion time and actual completion time of the road projects. The delay in the road projects lead to several risks such as cost overrun, legal issues, contract termination and many others. Application: Roads are the lifeline of a Country and its timely development plays a very important role in the Development of the Nation. This study will enable various parties involved to understand and mitigate the risks in a n effective manner.

Integrated production and preventive maintenance scheduling for a single machine with failure uncertainty

This paper addresses the problem of finding a robust and stable schedule for a single machine with availability constraints. The machine suffers unexpected breakdowns and follows the Weibull failure function. A joint model for integrating run-based preventive maintenance (PM) into the production scheduling problem is proposed, in which the sequence of jobs, the PM times and the planned completion times of jobs are proactively determined simultaneously. Aiming at optimizing the bi-objective of system robustness and stability, a genetic algorithm based on the properties of the optimal schedule is proposed. The experimental results demonstrate that the proposed algorithm is efficient and effective under practical problem sizes. In addition, the impact of degree of uncertainty on the performance and the tradeoff between robustness and stability are explored in detail.

Rescheduling with controllable processing times for number of disrupted jobs and manufacturing cost objectives

We consider a machine rescheduling problem that arises when a disruption such as machine breakdown occurs to a given schedule. Machine unavailability due to a breakdown requires repairing the schedule as the original schedule becomes infeasible. When repairing a disrupted schedule a desirable goal is to complete each disrupted job on time, i.e. not later than the planned completion time in the original schedule. We consider the case where processing times of jobs are controllable and compressing the processing time of a job requires extra processing cost. Usually, there exists a nonlinear relation between the processing time and manufacturing cost. We solve a bicriteria rescheduling problem that trades off the number of on-time jobs and manufacturing cost objectives. We give a mixed-integer second-order cone programming formulation for the problem. We develop a heuristic search algorithm to generate efficient solutions for the problem. Heuristic algorithm searches solution space by moving and swapping jobs among machines. We develop cost change estimates for job moves and swaps so that the heuristic implements only promising moves and hence generates a set of efficient solutions in reasonably short CPU times.

Using the Techniques of Decision-Making and Statistical Experiments Design in Prediction of the Random Factors Impacts on Implementation of Construction Project Plan

Accelerated development and use of decision-making technology, including the analytical hierarchy process (AHP) which has a high reliability to solve most of the uncertainty problems and meet their practical requirements, which enabled it to be used in a number of engineering and administrative applications. Statistical design of experiments technology is considered essential keys to deal with random data. Their important features enables us to combine them in a appropriate scenario to predict the prospects and rates of random factors and determine the extent of their impact on the delay for the implementation of a project. This research verified and reach the possibility of using these two techniques in the development of mutual influence between each of random factors, a very high correlation has been proved among such factors, where the correlation coefficient between them is equal to the value (1), a mathematical models that govern random factors effects was built by using of Statistical analysis of variance (Anova) and multiple linear regression to find mathematical models that found to be had a high resolution through R2 and F tests which gave (R2 = 1, F > = 1.18E +32) results. These models are used to build a scenario to predict the expectations of potential for the disposal of these factors during the annual monthly plan, and treatment to avoid random effects on the implementation of the project and the planned completion time.

Optimal project portfolio selection with carryover constraint

In a typical capital rationing problem, a project portfolio is selected to maximize expected return on investment while adhering to the capital budget constraint. Sometimes projects may be delayed and they have to be funded beyond their planned completion time. This type of ‘unplanned carryovers’ represents a financial obligation to the company. If future years' capital budgets cannot be expanded to cover such obligations, future projects may be cancelled or postponed to fund the unplanned carryover. In this paper, we develop a methodology based on multi-attribute utility theory and chance-constrained programming to optimize portfolio selection subject to the constraints that the selected portfolio does not exceed the available budget and that the carryover of the unspent funds to the next fiscal year does not exceed predetermined limits. We use this technique to select an optimal project portfolio for Lockheed Martin Space Systems' infrastructure investments.

Two Machine Scheduling under Disruptions with Transportation Considerations

Effective logistics scheduling requires synchronization of manufacturing and delivery to optimize customer service at minimum total cost. In this paper, we study a new scheduling problem that arises in a disruption environment. Such a problem occurs when a disruption unexpectedly happens, and consequently, some machines become unavailable for certain periods. Jobs that are assigned to the disrupted machines and have not yet been processed can either be moved to other available machines for processing, which may involve additional transportation time and cost, or can be processed by the same machine after the disruption. Our goal is to reschedule jobs so that an objective function, including the original cost function, and possibly transportation costs and disruption cost caused by deviating from the originally planned completion times, is minimized. In this paper, we focus on the two-machine case to demonstrate some major properties, and hope that these properties can provide insights for solving other general problems, such as multiple (more than two) machine scheduling and machine scheduling in other configurations (job shop or flow shop) under disruption. We study problems with different related costs. In each problem, we either provide a polynomial algorithm to solve the problem optimally, or show its NP-hardness. If the problem is NP-hard in the ordinary sense, we also present a pseudo-polynomial algorithm to solve the problem optimally.

Planned construction times and labour utilization — a comparison of UK and French contractors

The results of a model based survey of contractors' planning engineers in France and the UK suggest that planned completion times for constructing an identical high‐rise in situ concrete framed structure are significantly and dramatically lower in France than in the UK. Average planned construction periods in France were 13 weeks, some 9 weeks faster than the UK average of 22 weeks. Since planned construction periods reflect past experience, French contractors apparently achieve superior levels of production performance whilst at the same time working fewer hours per week, utilizing directly employed workers and employing fewer supervisors. If such planned completion times are truly representative, the findings indicate comparatively poor UK contractor performance, and signify future problems for the British builder in the emerging European marketplace. The causes of such poor performance are complicated, but based on indicative French best practices: production is enhanced when scheduled overtime is avoided, a directly employed and mainly skilled workforce is engaged, and a maximum working time of 40 hours per week is the norm rather than the exception.