Parametric estimation of supplier's plant construction costs

Cost engineers of buying enterprises perform detailed product cost calculations of externally manufactured components. The aim of these calculations is to determine what a product should cost and to support purchasing functions in fact-based negotiations. While product cost engineers have deep knowledge in the calculation of direct cost, they need support in the calculation of supplier´s indirect cost categories. The calculation of industrial rent, which is expressed in annual cost per m² of occupied plant building floor space can be improved by providing accurate construction cost estimates. Construction costs are strongly impacting the calculation of supplier´s annual building depreciation, which is a crucial cost driver for the determination of the industrial rent. Academic literature is actually not providing an accurate and suitable cost model for product cost engineers, which is estimating construction cost per m² depending on different industrial building categories and alternative supplier plant locations. The paper aims to close this gap by applying linear regression analysis on a set of European construction cost data considering two industrial building categories: “warehouses/basic factory units” and “high-tech factories”. By regressing construction cost against construction labor rates within different supplier plant locations it was possible to form suitable and accurate parametric regression functions with R² values between 0.74 and 0.88. Next to high R² values acceptable mean average percentage errors between 7.45% and 11.77% could be realized by comparing estimated with observed construction cost. The estimation of industrial construction costs based on the paper´s results can be used to improve the calculation of industrial rent, which is one cost element, that has to be covered within product cost engineer´s Should Cost Calculations.

Network traits predict ecological strategies in fungi

Colonization of terrestrial environments by filamentous fungi relies on their ability to form networks that can forage for and connect resource patches. Despite the importance of these networks, ecologists rarely consider network features as functional traits because their measurement and interpretation are conceptually and methodologically difficult. To address these challenges, we have developed a pipeline to translate images of fungal mycelia, from both micro- and macro-scales, to weighted network graphs that capture ecologically relevant fungal behaviour. We focus on four properties that we hypothesize determine how fungi forage for resources, specifically: connectivity; relative construction cost; transport efficiency; and robustness against attack by fungivores. Constrained ordination and Pareto front analysis of these traits revealed that foraging strategies can be distinguished predominantly along a gradient of connectivity for micro- and macro-scale mycelial networks that is reminiscent of the qualitative ‘phalanx’ and ‘guerilla’ descriptors previously proposed in the literature. At one extreme are species with many inter-connections that increase the paths for multidirectional transport and robustness to damage, but with a high construction cost; at the other extreme are species with an opposite phenotype. Thus, we propose this approach represents a significant advance in quantifying ecological strategies for fungi using network information.

Current Status of Old Housing for Low-Income Elderly Households in Seoul and Green Remodeling Support Plan: Economic Analysis Considering the Social Cost of Green Remodeling

In this study, the economic feasibility of green remodeling (GR), which could improve the health, safety, and energy of elderly households considering social cost, was analyzed. As a result, the net present value of GR was ‘−10,267 USD (49.7%)’, which was found to be uneconomical compared to the total construction cost (20,981 USD, 100%) despite benefits of energy saving, carbon reduction, and air pollutant reduction. Based on this result, in order to expand GR for low-income elderly households, who cannot afford to perform GR, a GR support measure linked to the currently implemented energy conversion and old-age housing support policies was proposed. It allows the government to perform GR for low-income elderly households with 1/4 of the total construction cost. This result could revitalize GR to reduce greenhouse gas and contribute to housing stability for low-income elderly households who are vulnerable to COVID-19 and climate change.

Quantification of Optimal Target Reliability for Seismic Design: Methodology and Application to Midrise Steel Buildings

Quantification of the optimal target reliability based on the minimum lifecycle cost is the goal standard for calibration of seismic design provisions, which is yet to be fully-materialized even in the leading codes. Deviation from the optimally-calibrated design standards is significantly more pronounced in countries whose regulations are adopted from the few leading codes with no recalibration. A major challenge in the quantification of optimal target reliability for such countries is the lack of risk models that are suited for the local construction industry and design practices. This paper addresses this challenge by presenting an optimal target reliability quantification framework that tailors the available risk models for the countries from which the codes are adopted to the local conditions of the countries adopting the codes. The proposed framework is showcased through the national building code of Iran, which is adopted from the codes of the United States, using a case study of three midrise residential steel building archetypes. The archetypes have various structural systems including intermediate moment-resisting frame (IMF) and special concentrically braced frame (SCBF). Each of these archetypes are designed to different levels of the base shear coefficient, each of which corresponds to a level of reliability. To compute the lifecycle cost, the initial construction cost of buildings is estimated. Next, robust nonlinear models of these structures are generated, using which the probability distribution of structural responses and the collapse fragility are assessed through incremental dynamic analyses. Thereafter, the buildings are subjected to a detailed seismic risk analysis. Subsequently, the lifecycle cost of the buildings is computed as the sum of the initial construction cost and the seismic losses. Finally, the optimal strength and the corresponding target reliability to be prescribed are quantified based on the notion of minimum lifecycle cost. The results reveal a 50-year optimal reliability index of 2.0 and 2.1 for IMF and SCBF buildings, respectively and an optimal collapse probability given the maximum considered earthquake of 16% for both systems. In the context on the case study of the national building code of Iran, the optimal design base shear for IMF buildings is 40% higher than the current prescribed value by the code, whereas that of SCBF buildings is currently at the optimal level.