A construction cost estimation framework using DNN and validation unit

Accurate construction cost estimation is crucial to completing projects within the planned timeframe and expenditure. The estimation process depends on multiple variables maintaining complex relationships between themselves and the target cost. As a result, an in-depth analysis from an experienced construction consultant is required to estimate construction costs accurately. Machine learning (ML) technology can learn from previous data, which is equivalent to human experience. Many project-specific ML models estimate the construction cost, which misses the generalizability. This paper addresses the gap and designs, develops, implements, and analyzes a deep learning (DL) based novel framework that maps 94.67% of the independent variables with a mean average percentage error (MAPE) of 11.60%. The proposed framework is not limited to any specific project. It estimates the construction cost of similar projects, further validated by an innovative estimator validation unit

Knowledge and agent-based system for decentralised scheduling in manufacturing

The aim of the research paper is to develop algorithms for manufacturers’ agents that would allow them to sequence their own operation plans and to develop a multi-agent infrastructure to allow operation pair agents to cooperatively adjust the timing of manufacturing operations. The scheduling problem consisted of jobs with fixed process plans and of manufacturers collectively offering the necessary operations for the jobs. Manufacturer agents sequenced and pair agents timed each operation as and when required. Timing an operation triggered a cascade of conflicts along the job process plan that other pair agents would pick up on and would take action accordingly. The conventional approach performs conflict resolution in series and manufacturer agents as well as pair agents wait until they are allowed to sequence and time the next operation. The limiting assumption behind that approach was systematically removed, and the proposed approach allowed manufacturers to perform operation scheduling in parallel, cutting down tenfold on the computation time. The multi-agent infrastructure consists of the Protégé knowledge base, the Pellet semantic reasoner and the Workflows and Agent Development Environment (WADE). The case studies used were the MT6, MT10 and LA19 job shop scheduling problems; and an industrial use case was provided to give context to the manufacturing environment investigated. Although there were benefits from the decentralised manufacturing system, we noted an optimality loss of 34% on the makespans. However, for scalability, our approach showed good promise

Towards decentralised job shop scheduling as a web service

This paper aims to investigate the fundamental requirements for a cloud-based scheduling service for manufacturing, notably manufacturer priority to scheduling service, resolution of schedule conflict, and error-proof data entry. A flow chart of an inference-based system for manufacturing scheduling is proposed and a prototype was designed using semantic web technologies. An adapted version of the Muth and Thompson 10 × 10 scheduling problem (MT10) was used as a case study and two manufacturing companies represented our use cases. Using Microsoft Project, levelled manufacturer operation plans were generated. Semantic rules were proposed for constraints calculation, scheduling and verification. Pellet semantic reasoner was used to apply those rules onto the case study. The results include two main findings. First, our system effectively detected conflicts when subjected to four types of disturbances. Secondly, suggestions of conflict resolutions were effective when implemented albeit they were not efficient. Consequently, our two hypotheses were accepted which gave merit for future works intended to develop scheduling as a web service. Future works will include three phases: (1) migration of our system to a graph database server, (2) a multi-agent system to automate conflict resolution and data entry, and (3) an optimisation mechanism for manufacturer prioritisation to scheduling services

The legacy of Verena Holmes: inspiring next generation of engineers

Verena Holmes was born in 1889 in Ashford, Kent, Verena became a pioneer for women in the industry as arguably the first female in the UK to have a full-time career as a professional mechanical, design and biomedical engineer. Verena was an advocate for widening participation in engineering and dedicated to the development of female engineers, she represented a breakthrough for equal rights in the early 20th century. As a creative and talented mechanical engineer, inventor and entrepreneur with own engineering business in Gillingham, Kent. In 1932, Verena Holmes filed a patent for poppet valve for fluid pressured systems, and in 2021 has provided the inspiration to students to conceive, design, implement and operate their own poppet valve. The poppet valve challenging first year biomedical, mechanical and product design engineering students to consider engineering materials, engineering manufacturing, standard components, fixes and fittings, and tolerances considerations into their poppet valve. This paper will provide qualitative analysis of the level of practical engineering learning, and the depth of student learning. Also, the quantitative analysis of the students’ evaluation of the learning opportunity to inspire, develop and stimulate them to be the next generation of engineers

Practice-based engineering design for next-generation of engineers: A CDIO-based approach

In recent years, practice-based learning has been establishing itself as a new norm in higher education: an enabler to foster knowledge, skills and innovative thinking in young learners. Conceive, design, implement and operate (CDIO), a well-established pedagogical methodology, offers many opportunities for education providers seeking to best achieve this practice-based learning within various educational environments. Case studies of engineering programs that made use of the CDIO model provide illustrations of how the ideas were put into effect in actual projects. This paper draws on a CDIO-based design case study where students were requested to solve a real engineering problem; in order to explore the great potential of such a teaching and learning paradigm in practice settings. Some first-year mechanical, biomedical and product design engineering students studying at the Canterbury Christ Church University were set a design brief by a Ford Motor Company tier supplier, to design a high security lock for commercial vehicles which works on both sliding and rear hinged slam doors. The project had twelve engineering groups, each with three or four students sharing responsibility for separate project design and engineering roles: including design sketches; computer-aided modelling; engineering material investigation; finite element analysis; computer-aided manufacturing; prototyping; project reporting and company presentation. In order to analyse the effect of incentives on the underlying motivation of learners, a cash prize was secured via the Engineers in Business Fellowship (EIBF) organisation, to be shared between the winners selected by the industrial partner after a detailed study of benefits, manufacturability and potential innovation. This paper documents the findings of collected qualitative and quantitative data as part of this project-based case study, and furthermore, reflects on the effectiveness of CDIO implementation on the depth of students’ knowledge and level of practical engineering learning. The objective here is to evaluate the individual and collaborative learning processes that occur among a group of students as they use CDIO active learning tactics. The analysis reported in this paper can serve as a foundation to illustrate how educators may better prepare their students for joining the workforce of the future, by using an active learning approach that provides more weight to practical than theoretical knowledge

Ontology-based decision tree model for prediction in a manufacturing network

This paper aims to create a predictive model, which will assist in the allocation of newly received orders in a manufacturing network. The manufacturing network, which is taken as a case study in this research, consists of more than 300 small manufacturing enterprises with a central company as the project managing integrator. The methodology presents the mapping of a PROSA (Product-Resource-Order-Staff Architecture) based ontology model on a decision tree, which was created with the Waikato Environment for Knowledge Analysis (WEKA) application. Furthermore, the methodology also demonstrates the formulation of the Semantic Web Rule Language (SWRL) rules from the WEKA decision tree with the help of MATLAB programming. The paper validated the result generated by the ontology model with the results of the decision tree model

Crystallization kinetics, structure and applications of PLA stereocomplexes

Résumé : Le poly(acide lactique) ou PLA est une famille de polyester thermoplastique linéaire qui a connu un essor commercial important durant la dernière décennie. L'enthousiasme pour le PLA vient de sa nature biosourcée, de ses bonnes propriétés mécaniques comme un module élastique élevé et de la possibilité de le biodégrader. Toutefois, certaines carences comme une faible résistance thermique et une faible élasticité à l’état fondu limitent son champ d’application. Fait à noter, le monomère d’acide lactique possède deux stéréo-isomères (L et D). Il est possible de polymériser les isomères L ou D pour former respectivement le PLLA ou le PDLA mais de façon surprenante, le mélange de PLLA et de PDLA permet la formation d’une structure cristalline distincte appelée le stéréocomplexe. Cette forme cristalline a un point de fusion 50[degré]C plus élevé par rapport aux formes cristallines du PLLA ou de PDLA d’où un premier intérêt pour augmenter la résistance thermique du matériau. Dans ce travail, l’usage de petites quantités (0-5 % massique) de PDLA comme additif dans une phase majeure de PLLA sera analysé. L’effet du stéréocomplexe formé à haute température sur la nucléation du PLLA et sur les propriétés rhéologiques du mélange sera plus particulièrement étudié. La présente thèse comprend une revue de littérature sur la cristallisation des PLA suivie de quatre parties expérimentales, conclusions et recommandations. La revue de littérature a pour objectif de réinterpréter l’ensemble des données disponibles sur la cristallisation du PLA afin d’en tirer des conclusions claires. La première partie expérimentale porte sur la cinétique de formation du stéréocomplexe à l'état fondu. Il a été constaté que la formation du stéréocomplexe est lente aux températures usuelles de mise en forme du PLLA ( 180[degré]C). De plus, la coexistence d’une morphologie baptisée dans ce travail « structure en réseau » et d’une morphologie sphérulitique a été révélée pour la première fois. Il a été démontré que la structure de réseau a une température de fusion moins élevée que la structure sphérulitique. Dans la seconde partie du travail, la cinétique de stéréocomplexation a été améliorée significativement pour adapter celle-ci aux cycles de refroidissement courts typiques des méthodes de mise en forme à l’état fondu. Ceci a été réalisé en ajoutant des agents nucléants qui initient la cristallisation à plus haute température et des agents plastifiants qui viennent augmenter la mobilité des polymères. Cette stratégie a permis de réduire le temps de cristallisation d’un ordre de grandeur. Dans un troisième temps, l'effet du stéréocomplexe sur les propriétés rhéologiques d’un mélange PDLA/PLLA a été investigué. En raison de son point de fusion élevé, le stéréocomplexe peut être préservé dans une matrice PLLA fondue et ainsi changer significativement les propriétés rhéologiques. La présence du stéréocomplexe a mené à une augmentation significative de la viscosité et de l'élasticité du PLA expliqué par la formation de points de « réticulation physique » dans la matrice amorphe. Enfin, dans la dernière partie expérimentale, le stéréocomplexe a été utilisé pour améliorer le comportement en moussage du PLA. Des expériences de visualisation et de moussage en mode discontinu ont montré que la présence de stéréocomplexe augmente la densité de nucléation de bulles et améliore significativement la morphologie de la mousse finale grâce à un effet de nucléation et à l’augmentation de l’élasticité du fluide. La revue de littérature et les trois premières parties expérimentales sont présentées sous forme d’articles scientifiques. La dernière partie expérimentale est à titre prospectif pour la suite du projet et ne sera pas soumise pour publication. // Abstract : Poly(lactic acid), or PLA, is a family of linear thermoplastic polyesters that has experienced strong market growth over the past decade. The enthusiasm for PLA originates from its bio-based nature, its good properties and its biodegradability. However, some of PLA deficiencies such as low thermal resistance and low melt elasticity have limited the development of this polymer. It is noteworthy that the lactic acid monomer has two stereo-isomers (L and D) that can be polymerized respectively into PLLA and PDLA but surprisingly, blending of PLLA and PDLA can lead to the formation of a “stereocomplex” which has a distinct crystalline structure from that of the homopolymers. This crystalline form has a melting point 50 oC greater than the crystalline PDLA or PLLA forms, thus it has by itself an interest in terms of heat resistance. In this work, the use of small amounts of PDLA (0-5%) in a matrix of PLLA will be explored. Particular emphasis will be on the nucleating ability of the stereocomplex (formed at high temperature) on PLLA crystallization and on its effect on the blends rheological properties. The current thesis comprises a literature review on PLA crystallization followed by four experimental sections. The objective of the literature review was to reinterpret the large body of data available on PLA in order to draw clear conclusions on PLA crystallization. The first experimental part of the work focused on the kinetics and conditions of stereocomplex formation in the melt state. It was found that stereocomplex formation is slow in the melt processing temperature range of PLLA (180 oC). Co-existence of a so-called “network structure” with a spherulitic structure was revealed for the first time. It was shown that the network structure has a lower melting point than the spherulitic one. In the second part of the work, stereocomplexation kinetics was improved significantly to match it with the fast cooling cycles typical of melt processing techniques. This was achieved by adding nucleating agents that initiated crystallization at higher temperatures and plasticizers that enabled more polymer fluidity. This strategy enabled an order of magnitude decrease in crystallization time. The third part of the work was the investigation of rheological properties upon formation of the stereocomplex structure in 0-5% PDLA in PLLA blends. Due to its higher melting point, the stereocomplex can be preserved in molten PLLA and alter significantly the blend melt rheology. Stereocomplex formation was monitored through rheological measurements and compared to classical calorimetry data. The presence of the stereocomplex lead to a significant increase in viscosity and in melt elasticity explained through the presence of physical crosslink points in the amorphous matrix. Finally, in the last experimental part of the work, the stereocomplex was employed to enhance PLA foaming behavior. Foaming visualization experiments as well as batch foaming tests showed that the presence of the stereocomplex can increase bubble nucleation density and led to a finer and more uniform foam morphology due to its nucleating effect and to the increased melt elasticity. The literature review and the three first experimental sections are presented in Peer-reviewed journal format. The last experimental section is meant as an exploratory and prospective part for the project and will not be submitted for publication

Malnutrition, Overweight, and Obesity among Urban and Rural Children in North of West Azerbijan, Iran

Introduction. Malnutrition is one of the most important causes for improper physical and mental development of children. Childhood obesity is a worldwide public health problem. The increasing prevalence of childhood obesity has become a growing matter of public health concern worldwide. The aim of the current study was to determine the prevalence of malnutrition and obesity in children under 5 years old in Salmas district. Methods. The current study is a cross-sectional study conducted on 902 of children under 5 years old to assess the nutritional status in Salmas district and performed from 16 until 30 October, 2011, with the cooperation of the Office of Community Nutrition Improvement and the United Nations Children’s Fund. ENA (Emergency Nutrition Assessment) and Spss software were used for data analysis. Results. 49.6% of children were boys and 50.4% were girls. The prevalence of malnutrition based on underweight, stunting, and wasting was estimated to be 2.3%, 7.3%, and 1.4% among children, respectively. Stunting was more common in rural areas and this difference was significant (P<0.001). Conclusion. In this area stunting, overweight and obesity were the most important priorities that health officials must pay more attention to. ENA software has a special ability to determine the samples and clusters and is a simple, rapid, and accurate method, especially in epidemiological studies in the country, and can be a convenient tool and its use is suggested for the same studies

A holonic workforce allocation model for labour-intensive manufacturing

This paper presents a new model for workforce allocation in labour-intensive industries. In such industries where production processes mostly include manual assembly operations, performance is highly influenced by the availability of skilled workers. Sudden unavailability of skilled labour has significant adverse effects on production. Furthermore, as competition intensifies, production becomes more sensitive to changing market demands. Such disturbances can be attenuated by introducing flexibility in the production planning process. Workforce allocation plays a significant role in the planning process. Thus, this paper focuses on workforce allocation, and a support system is developed from the concepts of holonic manufacturing systems and PROSA reference architecture. The system was designed in unified modelling language and was tested using an object-oriented software developed in C++. The use of the holonic methodology to develop the system has helped to identify the shortfalls of the conventional method adopted in industry and develop algorithms to improve the workforce allocation process. The proposed system was simulated using production data from a computer manufacturer case study. The paper then presents a comparison of the factory’s conventional method of workforce allocation with the proposed holonic workforce allocation system. The results suggest an improved manufacturing throughput performance