BIM as a generic configurator for facilitation of customisation in the AEC industry

One of the long-lasting challenges of the Architecture, Engineering and Construction (AEC) industry has been addressing personalised solutions as nearly affordable as possible to what could be offered by mass production in the post industrialisation era. Ever since its gestation, BIM has promised endless prospects for people, organisations, products and processes in the AEC industry. This paper sets out to investigate the benefits of BIM as a general configurator to facilitate customisation: offering personalised solutions at a price comparable to mass produced products and services. Providing a quick review of literature, the paper sets the scene for investigating how the generic capabilities of BIM applications can be utilised to offer customisable façade systems. Using a systemic approach, this is then used to elucidate future developments of the current project into next stages where other elements and parameters can be implanted into the basic family to broaden the choice and to reinforce this customisable façade solution.     

Integrated production planning and control system for a panelized home prefabrication facility using simulation and RFID

The construction industry is adopting off-site construction for its superior quality, short cycle time, and minimal environmental impact. Among the different off-site construction methods, panelized construction follows a manufacturing approach where houses are built in smaller panels in an assembly line. Due to the complex and unique nature of the home building process, existing manufacturing concepts such as automated production planning and control system are not applicable to the panelized home production facility. This paper utilizes radio frequency identification (RFID) technology, data mining, and simulation-based optimization to develop a production planning and control system for a panelized home production facility. The RFID system is used to automatically collect the production data; however, the RFID data in this study contains considerable noise. Thus, it is crucial to extract the relevant data from the raw data. A RANSAC model is developed for this purpose to automatically clean the RFID data and then use it to build the simulation model, which is then integrated with an optimization algorithm to generate the production schedule and real-time performance monitoring. The proposed framework cleans the noisy RFID data to extract records that represent a steady flow of assembly line. These clean records are then used to build PDFs that are required to develop discrete event simulation model that can help managers to capture an almost real-time snapshot of the production of the assembly line as well as automatically optimize the production schedule. The proposed system is implemented and validated in a panelized wall production facility operated by ACQBUILT Inc., a prefabricated home builder in Edmonton, Canada.     

Behavioural equivalence in simulation modelling

Discrete event simulation has grown up as a practical technique for estimating the quantitative behaviour of systems, where direct measurement is undesirable or impractical. It is also used to understand the detailed functional behaviour of such systems. Its theory is largely that of experimental science, centering on statistical approaches to validation, rather than on the verification of detailed behaviour. On the other hand, much work has been done on understanding and proving functional properties of systems, using techniques of formal specification and concurrency modelling. This article presents an approach to understanding equivalence of behaviour of discrete event simulation models, using a technique from the concurrency world, Milner’s Calculus of Communicating Systems (CCS). This yields a significant advance over the main previous work, Schruben and Yücesan’s simulation graphs. CCS allows for the use of observational equivalence, which can capture a more flexible, behavioural notion of equivalence than the structural equivalence defined there.A common framework based on the process view of models is constructed, using a hierarchical graphical modelling language (Extended Activity Diagrams). This language is shown to map onto both the major constructs of the DEMOS discrete event simulation language and the corresponding CCS models. A graphically driven tool based on such a framework is presented, which generates both types of models. Using the CCS model, behavioural equivalences and differences in simulation models are demonstrated.     

Optimization of simulated systems: OptQuest and alternatives

This article illustrates the general problem known as ‘simulation optimization’ through an (s, S) inventory management system. In this system, the goal function to be minimized is the expected value of specific inventory costs. Moreover, specific constraints must be satisfied for some random simulation responses, namely the service or fill rate, and for some deterministic simulation inputs, namely the constraint s < S. Results are reported for three optimization methods, including the popular OptQuest method. The optimality of the resulting solutions is tested through the so-called Karush–Kuhn–Tucker (KKT) conditions.     

A survey of dynamic parameter setting methods for nature-inspired swarm intelligence algorithms

Neural Computing and Applications - Parameter settings for nature-inspired optimization algorithms are essential for their effective performance. Evolutionary algorithms and swarm intelligence...     

Compressive strength of geopolymers produced by ordinary Portland cement: Application of genetic programming for design

In the present study, compressive strength results of geopolymers produced by ordinary Portland cement (OPC) as aluminosilicate source has been modeled by gene expression programming. Six main factors including NaOH concentration, water glass to NaOH weight ratio, alkali activator to cement weight ratio, oven curing temperature, oven curing time and water curing regime each at four levels were considered for designing. A total of 32 experiments were conducted according to the L32 array proposed by the method. The gene expression programming models were constructed by 10 input parameters including NaOH concentration, water glass to NaOH weight ratio, alkali activator to cement weight ratio, oven curing Temperature, oven curing time, water curing regime, water glass content, NaOH content, Portland cement content and test trial number. The value for the output layer was the compressive strength. According to the input parameters in the models, the constructed networks were trained and tested. The results indicate that gene expression programming model is a powerful tool for predicting the compressive strength of the geopolymers in the considered range.     

Best practice fusion of CMMI-DEV v1.2 (PP,PMC, SAM) and PMBOK 2008

ContextThe establishment of effective and efficient project management practices still remains a challenge to software organizations. In striving to address these needs, “best practice” models, such as, CMMI or PMBOK, are being developed to assist organizations interested in improving project management. And, although, those models share overlapping content, there are still differences and, therefore, each of the models offers different advantages.ObjectiveThis paper proposes a set of unified project management best practices by integrating and harmonizing on a high-level perspective PMBOK (4th ed.) processes and CMMI-DEV v1.2 specific practices of the basic project management process areas PP, PMC and SAM.MethodBased on the analysis of both models, a unified set of best practices has been defined by a group of researchers with theoretical and practical expertise on the CMMI framework and software process improvement as well as project management and the PMBOK. The proposed set has been revised by different researchers from different institutions in several review rounds until consensus was achieved.ResultsAs a result, a set of unified best practices is defined and explicitly mapped to the correspondent PMBOK processes and CMMI specific practices of the current versions of both models.ConclusionWe can conclude that an integration and harmonization of both models is possible and may help to implement and assess project management processes more effectively and efficiently, optimizing software process improvement investments.     

Symmetric caging formation for convex polygonal object transportation by multiple mobile robots based on fuzzy sliding mode control

In this paper, the problem of object caging and transporting is considered for multiple mobile robots. With the consideration of minimizing the number of robots and decreasing the rotation of the object, the proper points are calculated and assigned to the multiple mobile robots to allow them to form a symmetric caging formation. The caging formation guarantees that all of the Euclidean distances between any two adjacent robots are smaller than the minimal width of the polygonal object so that the object cannot escape. In order to avoid collision among robots, the parameter of the robots radius is utilized to design the caging formation, and the A⁎ algorithm is used so that mobile robots can move to the proper points. In order to avoid obstacles, the robots and the object are regarded as a rigid body to apply artificial potential field method. The fuzzy sliding mode control method is applied for tracking control of the nonholonomic mobile robots. Finally, the simulation and experimental results show that multiple mobile robots are able to cage and transport the polygonal object to the goal position, avoiding obstacles.