scholarly journals Visualising the Impact of Early Design Decisions on a Modular Housing Supply Network

2020 ◽  
Author(s):  
Victor Guang Shi ◽  
Ruby Hughes ◽  
Alison McKay ◽  
Richard Chittenden ◽  
Anthony Waller
Keyword(s):  
Supply Network ◽  
Housing Supply ◽  
Design Decisions ◽  
Early Design ◽  
The Impact ◽  
Modular Housing

Designing for adaptability: The Gateshead Civic Centre

2017 ◽  
Vol 35 (4) ◽  
pp. 380-396 ◽  
Author(s):  
Vladimir Ladinski
Keyword(s):  
Design Decision ◽  
Design Decisions ◽  
Content Type ◽  
Early Design ◽  
The Future ◽  
Borough Council ◽  
Potential Benefits ◽  
The Impact ◽  
Made In

Purpose The purpose of this paper is to examine the impact of early design decisions made in the 1980s upon the future adaptability of the Gateshead Civic Centre building and the implementation of a workspace strategy in the 2010s, and how they have supported the efficiencies achieved through the increase in office workspace numbers, and the associated advantages of accommodating more employees within the Civic Centre. Design/methodology/approach Available documents related to the original development of the Gateshead Civic Centre and the 2010s workspace-related adaptations were examined to establish potential links between the two, and compare the findings with designing for adaptability-related research. Findings The results show that the early design decisions made in the 1980s have contributed to the future adaptability of the building and thus facilitated the implementation of a workspace strategy within Gateshead Metropolitan Borough Council in the 2010s. In addition, they have supported the achievement of other efficiencies through the increase in office workspace numbers and location of more employees within the Civic Centre. The findings can guide future trends within the Council, as well as inform organisations on the potential benefits of designing for adaptability. Originality/value The study provides a prospective consideration of how an early design decision influenced the long-term adaptability of the building.

Quantifying the Impact of Sustainable Product Design Decisions in the Early Design Phase Through Machine Learning

2016 ◽  
Author(s):  
Addison Wisthoff ◽  
Vincenzo Ferrero ◽  
Tony Huynh ◽  
Bryony DuPont
Keyword(s):  
Environmental Impact ◽  
Product Design ◽  
Sustainable Design ◽  
Design Phase ◽  
Product Attributes ◽  
Design Decisions ◽  
Early Design ◽  
The Impact ◽  
The Relationship ◽  
Early Design Phase

As more companies and researchers become interested in understanding the relationship between product design decisions and eventual environmental impact, proposed methods have explored meeting this demand. However, there are currently limited methods available for use in the early design phase to help quantify the environmental impact of making design decisions. Current methods, primarily vetted Life Cycle Assessment (LCA) methods, require the designer to wait until later in the design phase, when a product’s design is more defined; alternatively, designers are resigned to relying on prior sustainable design experience and empirical knowledge. There is a clear need to develop methods that quantitatively inform designers of the environmental impact of design decisions during the early design phase (particularly during concept generation), as this allows for reexamination of decisions before they become costly or time-intensive to change. The current work builds on previous research involving the development of a search tree of sustainable design knowledge, which, applied during the early design phase, helps designers hone in on the impact of product design decisions. To assist in quantifying the impact of these design decisions, the current work explores the development of a weighting system associated with each potential design decision. The work presented in this paper aims to quantify the general environmental impact potential design decisions have on a consumer product, by using a multi-layer perceptron neural network with back propagation training — a method of machine learning — to relate the life-cycle assessment impact of 37 case study products to product attributes. By defining the relationship between LCA data and product attributes, designers in the early design phase will be more informed of which product attributes have the largest environmental impact, such that the designer can redesign the product to have reduce this impact.

Architecting Fail-Safe Supply Networks

2016 ◽  
Author(s):  
Shabnam Rezapour ◽  
Ramakrishnan S. Srinivasan ◽  
Jeffrey Tew ◽  
Janet K. Allen ◽  
Farrokh Mistree
Keyword(s):  
Service Level ◽  
Level Of Service ◽  
Supply Network ◽  
Flow Dynamic ◽  
Supply Networks ◽  
Uncertainty Sources ◽  
High Magnitude ◽  
Stochastic Events ◽  
Fail Safe ◽  
The Impact

A fail-safe network is one that mitigates the impact of different uncertainty sources and provides the most profitable level of service. This is achieved by having 1) a structurally fail-safe topology against rare but high magnitude stochastic events called disruptions and 2) an operationally fail-safe flow dynamic against frequent but low magnitude stochastic events called variations. A structurally fail-safe network should be robust and resilient against disruptions. Robustness and resilience respectively determine how well and how quickly disruptions are handled by the SN. Flow planning must be reliable in an operationally fail-safe supply network against variations to provide the most profitable service level to customers. We formulate the problem of designing/redesigning fail-safe supply networks as a compromise Decision Support Problem. We analyze the correlations among robustness, resilience, and profit for supply networks and propose a method for supply network managers to use when they need to find a compromise among robustness, resilience, and profit.

scholarly journals A conceptual simulation workflow to guide design decisions regarding the effects of daylight on occupants’ alertness

2021 ◽  
Vol 2042 (1) ◽  
pp. 012116
Author(s):  
Pierson Clotilde ◽  
Soto Magán Victoria Eugenia ◽  
Aarts Mariëlle ◽  
Andersen Marilyne
Keyword(s):  
Light Exposure ◽  
Well Being ◽  
Research Field ◽  
Decision Makers ◽  
Spectral Simulation ◽  
Design Decisions ◽  
Computational Tools ◽  
Recent Developments ◽  
The Impact

Abstract Recent developments in the lighting research field have demonstrated the importance of a proper exposure to light to mediate several of our behavioral and physiological responses. However, we spend nowadays around 90% of our time indoors with an often quite limited access to bright daylight. To be able to anticipate how much the built environment actually influences our light exposure, and how much it may ultimately impact our health, well-being, and productivity, new computational tools are needed. In this paper, we present a first attempt at a simulation workflow that integrates a spectral simulation tool with a light-driven prediction model of alertness. The goal is to optimize the effects of light on building occupants, by informing the decision makers about the impact of different design choices. The workflow is applied to a case study to provide an example of what learnings can be expected from it.

scholarly journals The Effect of Sappanwood Absorbance on Design Decisions

2020 ◽  
pp. 34-42
Author(s):  
Dan Pandapotan ◽  
Imam Djati ◽  
Meirina Triharini ◽  
Yusuf Maulana
Keyword(s):  
Surface Area ◽  
Raw Materials ◽  
Health Benefits ◽  
Design Decisions ◽  
Measurement Results ◽  
Repeated Use ◽  
Product Thickness ◽  
The Impact ◽  
Material Cutting ◽  
Color Texture

Sappan wood contains substances that have health benefits. The community has made use of sappan wood in various forms, such as powder and shavings. In addition, sappan products are found in the form of blocks and spindles. If the product is in the form of blocks or logs, then people can recognize several characteristics of a wood, such as color, texture, hardness and weight. This will be more difficult to do if the product is in the form of powder or shavings. These advantages can be utilized in forms that have a specific purpose, such as the use function and decoration function. The use function can be done by soaking sappan wood using water, at a certain temperature and time. The process will produce a solution with a certain content which can be measured based on the absorbance value. The decoration function can be carried out by forming the sappan wood using the chisel principle, reducing the volume of raw materials. This research was conducted to determine the impact of shape on the concentration of content in sappan wood, so that it produces considerations that can be used in designing a product made from sappan wood. Experiments were carried out on 4 types of treatments, N specimens representing the treatment of repeated use, LPA and LPB specimens representing different surface area treatments, and specimens V representing treatments with different volumes. Each treatment produced a solution which was measured using UV-Vis Spectorphotometry. The measurement results in each specimen solution show the absorbance value can be taken into consideration in designing a product made from sappan wood. The things that need to be considered are the distance between cavities, product thickness and material cutting patterns.

scholarly journals Social-network-based water supply network sectorization methodology using monte carlo simulation to predict economical and operational benefits

2017 ◽  
Vol 26 ◽  
pp. 44-53
Author(s):  
Enrique Campbell ◽  
Amilkar Illaya-Ayza ◽  
Joaquín Izquierdo ◽  
Rafael Pérez-García ◽  
Idel Montalvo
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Water Supply ◽  
Optimization Method ◽  
Supply Network ◽  
Water Supply Network ◽  
Water Supply Management ◽  
Net Profit ◽  
Short Run ◽  
The Impact

Water Supply Network (WSN) sectorization is a broadly known technique aimed at enhancing water supply management. In general, existing methodologies for sectorization of WSNs are limited to assessment of the impact of its implementation over reduction of background leakage, underestimating increased capacity to detect new leakage events and undermining appropriate investment substantiation. In this work, we raise this issue and put in place a methodology to optimize sectors' design. To this end, we carry out a novel combination of the Short Run Economic Leakage Level concept (SRELL- corresponding to leakage level that can occur in a WSN in a certain period of time and whose reparation would be more costly than the benefits that can be obtained). With a non-deterministic optimization method based on Genetic Algorithms (GAs) in combination with Monte Carlo simulation. As an example of application, methodology is implemented over a 246 km pipe-long WSN, reporting 72 397 $/year as net profit.

The impact of (S,s) policy on supply network performance: a simulation study

2012 ◽  
Vol 4 (2) ◽  
pp. 164 ◽  
Author(s):  
Eleonora Bottani ◽  
Gino Ferretti ◽  
Roberto Montanari ◽  
Giuseppe Vignali
Keyword(s):  
Simulation Study ◽  
Network Performance ◽  
Supply Network ◽  
The Impact
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