Total Development Cost Research Articles

Determinants of Social Responsibility Costs of Listed Manufacturing Firms in Nigeria

The study ascertained the determinants of social responsibility costs of listed manufacturing firms in Nigeria. Specifically, the study determined the relationship between firms' total assets and community development cost; total sales and staff development cost; and total equity and public utility cost respectively of listed manufacturing firms in Nigeria. The population of the study comprised all the 21 listed consumer goods manufacturing firms in Nigeria. Purposive sampling was applied in selecting the 15 consumer goods firms that made up the sample size for the study. Secondary data were collected from the annual reports of the sampled firms over a ten-year accounting period which spanned through 2013 to 2022. The Pooled Ordinary Least Square regression was used in testing the hypotheses. The findings of the study indicated that: there is a significant positive relationship between firms' total assets and community development cost of listed manufacturing firms in Nigeria (p-value = 0.0059); there is a significant positive relationship between firms' total sales and staff development cost of listed manufacturing firms in Nigeria (p-value = 0.0000); there is positive but non-significant relationship between firms' total equity and public utility cost of listed manufacturing firms in Nigeria (p-value = 0.7002). Based on the findings, it was generally recommended in the study that firms should prioritise their investment in social responsibility as their financial metrics progress so as to enhance their reputation and strengthen their relationship with their host communities and stakeholders.

Economic Analysis and Feasibility of Self-propelled Rotor Power Weeder

The manual weeding process is laborious, requires significant effort, and is a costly operation. Farmers typically allocate 30 to 40 percent of their total crop production expenses to the weeding process. The research was carried out by development and economic feasibility of self-propelled weeder for small category farmers. Economic analysis and feasibility of developed mechanical weeder was evaluated by considering cost of operation, breakeven point and payback period. The utilization of a self-propelled weeder for mechanical weeding can result in cost savings of up to 45% compared to the manual weeding method. The estimated break-even point (BEP), calculated based on time and area, indicates potential savings of 209.6 hours and 13.63 ha. The payback period, assessed on a time basis for the rotary power weeder, was determined to be 1.02 years. The total development cost for the self-propelled power weeder was recorded as 8050 Rupees. By adopting self-propelled power weeder, farmer saving 1856 ₹/ha directly over manual method.

Land, landowners, and the delivery of affordable homes on rural exception sites in England

Land is a major part of the total cost of residential development, particularly in advanced economies where significant proportions of economic value resolve to land and where land for development is rationed through planning systems that seek to corral extractable value into specific locations, in support of the infrastructure investment needed to unlock development opportunity. In England, strong markets assign a high value for land allocated for housing in local plans, relative to unallocated land. In England’s rural areas, constraints on land development – for reasons of landscape and amenity protection, or to support food security – contribute to significant affordability challenges for households on lower rural wages, who may be out-competed in the housing market by adventitious purchasers, or simply by more affluent buyers bidding for a limited supply of rural homes. Planned development (on sites allocated in a local plan) may not meet the needs of lower-income groups in constrained rural housing markets. For that reason, it is necessary to support housing affordability by granting exceptional permission for development on unallocated land, and then negotiating land sales at a price that will allow a non-profit housing provider (a ‘registered provider of social housing’) to build affordable rented homes for local households in need. Development on ‘rural exception sites’ (RES) has a thirty-year history. It is an important means of supporting the development of affordable homes in smaller villages (market-led schemes on allocated sites are the norm in larger settlements, with affordable homes procured through agreement with for-profit developers). The RES approach lays bare the impact of land cost on housing affordability. Only if a sufficiently low price for land, which is well below ‘full residential’ value, can be agreed will it be viable to develop affordable homes, with rents matching local wages. Where such a price is agreed, it may be possible to build homes without cash subsidy. If the price rises, affordability may be threatened, unless public grant support is more generous or market homes on the RES can be used to mitigate a higher land cost by providing cross-subsidy for affordable homes. This monograph details research exploring the recent granting of exceptional planning permissions in England, the critical relationship with landowners, and how those landowners may be incentivized to sell land at a price that supports affordability. It analyses extant threats to the approach, and therefore the risk that a key mechanism for delivering affordable homes may be undermined by a market logic that continuously questions the efficacy of ‘non-market’ and ‘non-profit’ housing solutions in England.

Operational AI analysis flows: A framework for the efficient integration and execution within test processes

The European Commission’s “Flightpath 2050” highlights the critical role of the design phase in complex aircraft development. Ensuring the aircraft’s functionality, particularly for certification, represents a significant proportion (around 50%) of the total development cost. The increasing complexity of the testing process presents challenges. For example, the creation of simulation models for HIL testing and the performance of exploratory tests for certification are becoming increasingly complex due to the growing complexity of aircraft design.To address this challenge, this research aims to integrate AI modelling and data analysis into aircraft test processes as part of the design process. The aim is to develop a user-friendly modelling tool for test engineers without the need for data analyst expertise. The approach focuses on achieving seamless interoperability and easy integration of test-related data sources and AI models, eliminating the need for complex scripting in scripting languages such as Python or Matlab. To achieve this goal, a domain ontology and generic wrappers have been developed to map generic AI models to the TensorFlow and Matlab tools. At the same time, data sources are connected via a data integration tool.The evaluation successfully demonstrates the ability to analyse the correlation between sensors in an experimental cooling system without understanding the data format of the data sources and without the scripting of the AI model to model and execute the AI models.

Best Practices to Achieve Optimal Geothermal Drilling Performance in A Cost-Effective Manner: Case Study of the Fastest Geothermal Well Drilling in Java and Sumatra

Indonesia, recognized for possessing substantial geothermal energy potential, is working towards harnessing the resource to achieve numerous objectives. Among the primary challenges encountered is the considerable expense of geothermal drilling. One of the most significant obstacles to achieving this objective is the high drilling cost, which constitutes 35-40% of the total cost of geothermal energy development. The drilling cost is mainly affected by the time needed to drill one well because the faster the time, the lower the cost. Therefore, this research analyzed drilling activities, identified the fastest and most effective methods for optimal geothermal drilling performance, and reduced costs. The research also determined the factors that contributed to the sustained status of Well X as the fastest well drilled in the past decade. The methodology comprised literature review, data collection through adequate background on well and geothermal field, and data analysis. The result showed that the fastest drilling operation of a geothermal well in Indonesia in 2012 occured in West Java (Well X) for only 9.9 days with 1736.5 meters (mMD). Meanwhile, in 2021, Well Y in Sumatra spent 21.74 days to reach a depth of 2200 mMD. The use of a single-run and clean-out Bottom Hole Assembly (BHA) throughout the entire section affected the drilling duration and significantly reduced the inner side cleaning time, respectively. The cost of Well Y drilling, achieved using the best performance of two wells, reduced drilling costs by 19.2%.

Project Cost Estimation Using a Stepwise Approach: a Case Study of an Infrastructure Project in Gresik Regency, East Java

There are many studies related to cost estimation applied in a project, but only a few employ using “stepwise” method. This approach is expected to assist in solving complex problems by establishing a criteria hierarchy, subjectively assessed by interested parties, and incorporating various considerations to develop weights or priorities. The foundation of the stepwise approach relies on well-documented findings, which assert that 80% of the total project cost corresponds to the 20% most expensive components of the work. The research systematically collected data for project development estimates based on the bill of quantities from each year, as well as the HSPK (activity main unit price) in Gresik Regency from 2016 to 2018. This research aims to develop a conceptualized estimation model that provides clear, rapid, and relatively accurate initial project cost information. The results of this research include analysis of stepwise approach on cost realization, analysis of accuracy of the cost estimation model for buildings using the stepwise method, and an analysis of the cost of road and bridge infrastructure projects to facilitate completion in Gresik Regency. The research concludes that the analysis of the Cost Significant Model's impact on cost realization in the Public Works and Spatial Office's Highways Division in Gresik Regency has resulted in a cost estimation model for road development with an accuracy range from -12.7% to 16.0%, with an average accuracy rate of 0.59%. Additionally, there is a very strong correlation (R) of the independent variable (work in Division 2) and the total development cost, indicating that fluctuations in the cost of significant components are closely linked to changes in the overall development cost. The analysis of infrastructure project costs related to roads and bridges for project completion revealed that the highest value among independent variables is associated with Division 7, at Rp. 4,403,054 per m2. This suggests that the cost of Division 7 work is the most influential, while Division 1 (X1) has the lowest cost, at Rp. 35,589 per m2. Furthermore, there is a work component with zero cost, namely, Division 4 works.

On the installation effects of open ended piles in chalk

Chalk is a highly porous rock formed by cemented calcite grains. It covers areas of the UK and is widespread under the North Sea where offshore wind turbines (OWT) are currently being installed and where future offshore expansion will be sited (Figure 1(a)) [1]. Large piles are often driven in chalk to support OWT. The installation process causes the intact rock below the pile tip to crush into a putty characterised by a mechanical behaviour very different from the intact chalk. The difficulty to predict the final state of the putty and the stress around the pile after installation is the underlying reason for inadequate current design guidance for piles in chalk. Considering that for OWT, foundations account for 20-25% of the total development cost , pile design improvements in chalk, would be extremely beneficial from an economical and environmental perspective.
 Current guidelines for the design of piles in chalk (CIRIA C574) originate from the analysis of a limited number of pile tests [2]. These guidelines suggest crude average ultimate unit shaft friction (tsf) design values of between 20 and 120 kPa for low-medium density and high/very-high density chalk, respectively. tsf estimates are thought to be conservative hence introducing significant increases in cost and carbon footprint (Figure 1(b)). Reducing the level of conservatism (e.g. enabling more confident use of higher tsf) would reflect in significant savings of steel and consequent reduction of the cost and embodied carbon. Such design considerations are possible but require a better understanding of the long-term mechanical behaviour of the damage processes intact chalk experiences during dynamic installation in hydro-mechanical (HM) coupled conditions.
 In this work the coupled HM effects developing during pile installation in chalk are investigated numerically using a robust and mesh-independent implementation of an elasto-plastic constitutive model at large strains. The model, implemented into an open-source Geotechnical Particle Finite Element (G-PFEM) code [3], is shown to be able to capture the damage of the rock until the formation of a chalk putty layer around the shaft of a model piles jacked in chalk. In particular the complex flow processes occurring in the soil around both open and closed ended piles of variable shape jacked into saturated chalk are investigated. A fully coupled hydro-mechanical formulation, based on regularized, mixed low-order linear strain triangles is used [5]. To capture the relevant features of the mechanical response of chalk, a finite deformation, non-associative structured modified cam clay is used [6]. The model formulation is based on a multiplicative decomposition of the deformation gradient and on the adoption of an elastic response based on the existence of a suitable free energy function. Bonding-related internal variables, quantifying the effects of structure on the yield locus, are used to provide a macroscopic description of mechanical destructuration effects. To deal with strain localization phenomena, the model is equipped with a non-local version of the hardening laws [7]. The G-PFEM model is shown to be capable of capturing the destructuration associated with plastic deformations below and around the pile shoulder; the space and time evolution of pore water pressure as the pile advances; the effect of soil permeability on predicted excess pore water pressures, and the effect of chalk putty formation on predicted values of the load displacement curve. Installation effects are highlighted by comparing the axial performance between wished in place piles and piles which considered the full installation process.

Analyze the Performance of Software by Machine Learning Methods for Fault Prediction Techniques

Trend of using the software in daily life is increasing day by day. Software system development is growing more difficult as these technologies are integrated into daily life. Therefore, creating highly effective software is a significant difficulty. The quality of any software system continues to be the most important element among all the required characteristics. Nearly one-third of the total cost of software development goes toward testing. Therefore, it is always advantageous to find a software bug early in the software development process because if it is not found early, it will drive up the cost of the software development. This type of issue is intended to be resolved via software fault prediction. There is always a need for a better and enhanced prediction model in order to forecast the fault before the real testing and so reduce the flaws in the time and expense of software projects. The various machine learning techniques for classifying software bugs are discussed in this paper.

Off-plan property sales as an innovative financing option in real estate development

Real estate development is fraught with many uncertainties leading to serious shortages particularly of affordable housing for the majority of urban population. As a consequence, development developed a fairly innovative financing strategy – off plan sales. The strategy has emerged as an alternative source of finance, presenting developers with a chance to obtain funds from would-be buyers of the units in their proposed development. In spite of the huge significance of off-plan property sales and its growing popularity in the global platform, there is limited knowledge in this strategy as a financing option. The paper aims at sought to determining the challenges and constraints of off-plan property sales, as a financing strategy to the developers and as an investment to the property buyers and recommending appropriate mechanisms of enhancing it. Data was collected through a combination of different tools including questionnaires and key informant interviews. The study established that off-plan sales is an effective mode of financing real estate development since it generates significant savings on the cost of development, mainly through savings on interest to the tune of between 4% - 8.5% of the total cost of development. In the end, it emerged that the success of financing through off plan sales requires among others: establishment of an optimal mix in financing options; careful planning; early and vigorous marketing of the development; pre-qualification of potential off-plan buyers; the need for due diligence by buyers prior to purchase of the off-plan units; and the need for legal framework regulating off-plan sales.

Use of Neural Networks and Computer Vision for Spill and Waste Detection in Port Waters: An Application in the Port of Palma (MaJorca, Spain)

Water quality and pollution is the main environmental concern for ports and adjacent coastal waters. Therefore, the development of Port Environmental Management systems often relies on water pollution monitoring. Computer vision is a powerful and versatile tool for an exhaustive and systematic monitoring task. An investigation has been conducted at the Port of Palma de Mallorca (Spain) to assess the feasibility and evaluate the main opportunities and difficulties of the implementation of water pollution monitoring based on computer vision. Experiments on surface slicks and marine litter identification based on random image sets have been conducted. The reliability and development requirements of the method have been evaluated, concluding that computer vision is suitable for these monitoring tasks. Several computer vision techniques based on convolutional neural networks were assessed, finding that Image Classification is the most adequate for marine pollution monitoring tasks due to its high accuracy rates and low training requirements. Image set size for initial training and the possibility to improve accuracy through retraining with increased image sets were considered due to the difficulty in obtaining port spill images. Thus, we have found that progressive implementation can not only offer functional monitoring systems in a shorter time frame but also reduce the total development cost for a system with the same accuracy level.

Metaheuristic algorithm for the construction of mixed covering arrays of different strength levels to be used in the design of black box software test cases

Introduction— Currently, software quality is a fundamental feature to ensure a space in the global market that day by day is more competitive and demanding. Software testing allows software developers to find and fix bugs and, thereby, raise the quality of their products. The cost of testing is now estimated at 50% of the total cost of software development, so it is necessary to find less expensive ways to ensure elevated levels of fault detection. In this scenario, black box tests play a key role; within these tests, combinatorial approaches are one of the best options. In combinatorial tests, test users must have a tool that provides them with the least number of test cases with the greatest coverage (failure detection) according to the parameters of the method (procedure, function, or other) that they want to test, and this is the main objective of this work. Objective— This paper presents an algorithm that supports the generation of test cases in black box tests based on the creation of Mixed Covering Arrays (MCA). These fixes allow you to generate the smallest number of test cases required to test a unit of code with the highest required coverage. The proposed algorithm builds an initial solution based on a greedy algorithm and then improves this solution through an iterative process oriented by simulated annealing (metaheuristic algorithm). Methodology— The research was conducted following the Iterative Research Pattern proposed by Pratt. First, the main problems reported in the state of the art for the construction of CSF were identified, then a review of the proposed solutions to these problems was performed. Then a first algorithm was created and then iteratively modified this algorithm, including, and removing components according to the experimental results of its operation. When the desired version was obtained, a process of refinement of parameters was performed and compared with the best results presented in the literature, results obtained by different algorithms. Results— The proposed algorithm obtains MCAs that are competitive (on average 3 additional test cases) against the best reported in the state of the art in an abbreviated execution time, an aspect that is of special interest for software testers. Conclusions— It was confirmed that the greedy and metaheuristic approach based on simulated annealing is a suitable alternative for the construction of a CSF. Neighboring solution construction algorithms are key to finding the required MCA in a shorter execution time.

A cost-consequence analysis of eLearning videos designed to supplement the consent process in lower limb arthroplasty.

Since the Montgomery ruling in 2015 surgeons have been tasked with identifying material risk when taking informed consent. Despite this, there has been limited uptake of technological aids to supplement the consent process although such aids are shown to improve patient knowledge and satisfaction. ConsentPLUS is a free-to-access website with bite-sized educational videos designed to clearly explain lower limb arthroplasty procedures to patients and aid their consent. The authors performed a prospective cost-consequence analysis, outlining any costs associated with the intervention and any quantitative or qualitative impacts the intervention may have on patients. A total of 3,143 consecutive patients were identified who were undergoing total knee or hip replacement in 25 elective NHS orthopaedic units. The total cost of development and projected 10-year running fees for ConsentPLUS total £75,000. Health Foundation support means the service is free-to-access for centres throughout the UK. Mean exposure time per patient was 10min 29s, equivalent to £185,437 of additional contact time according to the National Tariff. Mean clinic time was reduced by 17min owing to the earlier identification of material risk. Patient knowledge on pre- and post-video quizzes increased from 7.01 to 9.08 following eLearning (paired t-test = 0.998). The process had an overall satisfaction rate of 97%. Educational eLearning videos are an accessible and digestible way to supplement the consent process. This enables earlier identification of material risk in clinics owing to improved patient knowledge, leading to increased patient satisfaction with arthroplasty consenting.

Advanced Statistical Methods in Spacecraft Flight Software Cost Estimation: Bayesian Regression and Nonlinear Principal Components Analysis to Support System Engineering in the Early Project Lifecycle

AbstractThis paper provides an overview of the new features and model updates in the upcoming release of the NASA Analogy Software Cost Tool (ASCoT). ASCoT, hosted within the Online NASA Space Estimation Tools (ONSET) on the One NASA Cost Engineering (ONCE) Database, is a web‐based tool that provides a suite of estimation tools to support early lifecycle NASA flight software cost analysis. In addition to the traditional parametric flight software costing method CO‐COMO II, ASCoT contains a Bayesian linear regression to predict total flight software development cost as a function of total spacecraft cost, as well as four analogic methods: k‐Nearest Neighbors (kNN) and Clustering models to predict Effort (in work‐months) and total source lines of code (SLOC). These methods are designed to work primarily with system‐level inputs such as mission type (orbiter, lander, etc.), mission destination (Earth, Inner Planetary, etc.), and the number of instruments and deployables. Nonlinear principal components analysis (NLPCA) is performed to find the principal features of the data composed of both categorical and numerical variables and is necessary prior to defining our analogic methods. Sensitivity analyses and in‐ and out‐of‐sample model performance results are presented for the Bayesian CER and the analogic models.

Macro-engineering Design for an Artificial Lake in Southeastern Jordan

Water situation in Jordan has become very critical. A feasible solution is to desalinate water drawn from Gulf of Aqaba (GoA). Another problem that Jordan faces is the very short coastline. These two problems can be solved by developing an artificial lake in south Jordan. The water from the lake can be desalinated while the lake itself provides a badly needed coastline. This work presents a macro-engineering design for the proposed lake; The proposed project is named "Red Sea-Jafer Basin Conduit (RSJBC)"; it involves a pipeline connecting GoA at the Red Sea with Jafer Basin (JB) in the south-eastern desert, where the topography of the region is exploited to develop an artificial Lake. Using multiple pumping stations, seawater will be pumped from GoA to JB though a 220 km long pipeline. After constructing the project, it will take three years to fill-up the Lake. Once it is filled, the pumping rate is reduced from 51 to 30 m3/s. However, based on fresh water needs, a volume of up to 21 m3/s can be desalinated. The suggested pipeline route has a curved path (CP) to avoid the mountains if it were to go straight path (SP). A comparison is conducted between CP and SP, where it was found that CP offers the lowest development cost for RSJBC, given fabric pipe is used. More specifically, a pipe diameter of 6 m enables total development cost of 2.74 B$, with corresponding annual operating cost of 306 M$.

FEASIBILITY INVESTING IN DEVELOPMENT PROJECTS CITRA HARMONI SHOP (PT CIPUTRA TBK)FEASIBILITY INVESTING IN DEVELOPMENT PROJECTS CITRA HARMONI SHOP (PT CIPUTRA TBK)

Investment is a commitment to several funds or other resources carried out at this time, intending to obtain some benefits in the future. Investments can be associated with a wide variety of activities. Investing many funds in real assets (land, gold, machinery, or buildings) or financial assets (deposits, stocks, or bonds) is an investment activity that is generally carried out, especially for developers. So that before stepping into the development stage, it is necessary to conduct a feasibility study first to be able to state whether or not the development of a project is continued.
 This study takes a case study of RUKO (Rumah Toko) in the Sidoarjo area, namely Ruko Citra Harmoni, and in its financial analysis uses discounted cash flow analysis.
 From the analysis results obtained: (1) Total development costs (development costs) calculated from the cost of DC phase, I added to the DC phase II is Rp. 3,831,665,014, -. (2) Loan from 60% development cost (DC) which is Rp. 2,298,999,008,-, while the remaining 40% of Rp.1,532,666,006,- is equity. So that the Debt Service from the loan that must be paid annually is Rp. 285,075,877,-. (3) The net present value obtained is Rp. 1,389,027,781,- during 30 years. (4) Internal rate of return (IRR) = 18.47 % > discount factor (DF) 16%. (5) Payback period is 23.8 years. (6) BCR > 1, i.e. 1.29 > 1. So from the several assessments above it can be stated that the Royal Business Regency Ruko Palm Project is feasible to work on and carry out construction

A Framework for Improving Software Maintenance Using World Class Manufacturing Methodology

The software that is being developed is becoming more complex and huge. The software industry has a huge problem with software maintenance. During the initial stages of software development, it becomes necessary to identify the ease with which a software system or component can be modified to correct faults, increase performance or adapt to a changing environment, i.e. software maintainability. This aids in the reduction of maintenance costs. A software is developed for some particular purpose, which may or may not change depending on the needs of the customer or the technological process. Hence, it leads to the evolution of the software to fit with the changing requirements. This non-trivial problem requires significant attention. According to some surveys, software maintenance accounts for about 80% of total software development costs. Therefore, this paper proposed a framework to integrate various World Class Manufacturing (WCM)-based technologies to create a model that can be utilized for improving maintenance, reduce time and cost of software maintenance

The Effect of Geographical Conditions on the Role of the Special Autonomy Fund for the Availability of Road Infrastructure in Papua

This study identifies the relationship of the Special Autonomy Fund (DOK) to Road Infrastructure by looking at variations in the Construction Cost Index as a proxy that describes the geographical conditions in Papua. Infrastructure development is a sector that is expected to accelerate the provision of basic infrastructure to reduce the development gap. However, the success of infrastructure development in Papua is inseparable from geographical factors. By using data from 29 regencies/cities in Papua Province and 11 regencies/cities in West Papua Province from 2010 to 2020, to determine the correlation of the Special Autonomy Fund on Road Infrastructure, the fixed effect panel data method and the moderating regression model were used to see if the moderating variable Construction Cost Index can strengthen or weaken the relationship of the Special Autonomy Fund to Road Infrastructure. This study found a positive relationship between the Special Autonomy Fund on Road Infrastructure and identified a negative moderating of the Construction Cost Index variable on the relationship of the Special Autonomy Fund to Road Infrastructure. This shows that the higher the Construction Cost Index, the higher the price of construction materials, increasing the total cost of road infrastructure development. As a result, the Special Autonomy Fund allocated is only able to buy fewer road construction materials, which has an impact on the reduced quantity of road infrastructure built in the provinces of Papua and West Papua.

Determinants of the Economic and Financial Feasibility of Real Estate Development Projects: A Comparative Analysis between Public and Private Development Projects in South Korea

We analyse the factors involved in the selection of a development site to secure the economic feasibility and profitability of a public development real estate project through a comparative analysis with private development projects. Logistic regression was used as the analysis method. In the case of public development projects, whether or not the investment screening passed was used as a dependent variable, and in the case of private development projects, the successful bid rate was used as a dependent variable. Independent variables were selected based on prior research on variables suitable for the purpose and situation of the project. The results show that the greater the total development costs of a public development project and the greater the size of a private development project, the greater the rate of approval and bidding success. For public projects, the rate of approval decreases when there are several subways, train stations, and supermarkets; however, this is not the case for private projects, owing to differences in development methods and project purposes. From a public standpoint, the balanced regional development, revitalisation of old city centres, and implementation of social overhead capital projects in neighbourhoods lacking infrastructure have a strong influence. From a private sector perspective, the mobile/resident population, modification in extra demand, and feasibility analysis have a strong influence. In sum, if the private sector avoids large-scale supermarket projects, they can be conducted as public development projects to enhance residents’ quality of life and revitalise the regional economy. Researchers should examine what could be benchmarked in the private sector in the operational stage and explore ways to maximise profitability and reduce financial burden.

Multiobjective multistage robust integer optimization model and algorithm for oilfield development planning

This paper discusses the long-term planning problem of oilfield development. The planning aims to deploy the workload of stimulation treatments with uncertain indicators. And the uncertainties of initial stimulation effect, annual effect error and new recoverable reserves are considered. With their uncertainty sets and the adaptability of decisions, a multiobjective multistage robust integer optimization model is constructed. In this model, the total development cost is minimized and the total new recoverable reserves is maximized. And the model makes decisions on the workload of each stimulation treatment in each year under constraints of annual oil production and workload balance. In addition, an algorithm for solving multiobjective multistage robust integer optimization model is proposed, which can obtain the finitely adaptive robust efficient solution set. Finally, a numerical example of long-term oilfield development planning is presented. The planning model with given uncertainty sets is solved, to verify the validity of the proposed model and algorithm.

An overview on the influence of process parameters through the characteristic of 3D-printed PEEK and PEI parts

Fused Filament Fabrication (FFF) technology is increasingly applied in automotive, aerospace and medical applications. FFF is one of the most widely used additive manufacturing techniques to manufacture thermoplastics or their composites. FFF enables improvement in both cycle time and total cost of product development. Such improvements are achieved through the quick manufacture of functional prototypes enable real-world product development and testing. While the benefits of FFF are undeniable, its use in demanding applications is hindered by materials properties. The used commodity and standard polymers actually exhibit low to medium thermal and mechanical properties. To overcome this limitation, the aerospace industry looks for high-performance thermoplastics to obtain plastic parts strong enough to be used as a replacement for metal. Recent developments in FFF equipment now enable engineering polymers, such as Polyether ether ketone (PEEK) and Polyether imide (PEI), to be utilized for parts with increased mechanical and thermal properties. Thus, this article reviews and discusses the properties and the printing parameters of PEEK and PEI produced by FFF.