Identifying stakeholders’ roles and relevant project documents for 4D-based collaborative decision making

To fully understand and effectively implement 4D building information modelling (BIM) models and methods, we need to develop a precise knowledge of which project digital documents should be used and how they influence the decision-making (DM) process. This article studies the convergence between uses of 4D BIM and digital project documents. We hypothesize that a clear visualization of the construction simulation through a 4D model is a useful source of information and a support for DM at collaborative meetings. Through this research, we continue to progress toward a new 4D-based collective decision device, so these elements will contribute to propose 4D BIM as DM support on architecture engineering construction (AEC) projects. Further, the present research will be complemented by results from questionnaires given at a later research stage. The article presents a brief review of BIM context to consider ways of fostering the implementation of all 4D BIM uses (not only visualization). It then introduces a proposition for 4D BIM uses implementation by the project development phase. It concludes by summarizing stakeholders’ roles and documents relevant to 4D BIM uses.     

Modelling and analysis of business process reengineering

Business process design and business process reengineering (BPR) depend crucially on linking production procedures and organizational services to business goals and objectives. There is currently very little formula support for this kind of reasoning as analytical tasks are usually carried out informally and individual design decisions are hard to relate to business objectives. If BPR is carried out without understanding the way it is done, then the most likely outcome would be continuing less-than-satisfactory current practice and automating outdated processes. This kind of practice misses opportunities for innovation and rationalization. The modelling and analysis of business processes along with business strategies and organizational structures are essential to study the implications of BPR. In this paper, an attempt has been made to study the modelling, analysis and tools/techniques used for modelling of BPR with the help of a survey on the recently (1993-2000) employed methods and tools used for BPR modelling and analysis. A framework for modelling and analysis, and guidelines for the selection of tools/techniques of business process reengineering are presented.     

Survey of methods to visualize alternatives in multiple criteria decision making problems

When solving decision problems where multiple conflicting criteria are to be considered simultaneously, decision makers must compare several different alternatives and select the most preferred one. The task of comparing multidimensional vectors is very demanding for the decision maker without any support. Different graphical visualization tools can be used to support and help the decision maker in understanding similarities and differences between the alternatives and graphical illustration is a very important part of decision support systems that are used in solving multiple criteria decision making problems. The visualization task is by no means trivial because, on the one hand, the graphics must be easy to comprehend and not too much information should be lost but, on the other hand, no extra unintentional information should be included. In this paper, we survey and analyze different ways of visualizing a small set of discrete alternatives graphically in the context of multiple criteria decision making. Some of the ways discussed are widely used and some others deserve to be brought into a wider awareness. This survey provides a starting point for all those who deal with multiple criteria decision making problems and need information of what kind of visualization techniques could be put to use in order to support the decision maker better.     

Manufacturing supply chain modelling and reengineering

The first-wave of reengineering, during the first half of the nineties, focused on making organizational changes and used primarilyinformation models of supply chains to integrate business processes.Quantitative models are expected to have a significant impact in the second-wave of reengineering through the deployment of performance and optimization models, economic analysis, and decision support systems. In this paper, we focus on the vital role that quantitative modelling techniques such as those founded in Operations Research and Industrial Engineering can play in reengineering supply chains. These quantitative models can extend the business process reengineering concepts to provide a concurrent reengineering framework for modelling the supply chain processes, identifying reengineering opportunities, evaluating design alternatives, guiding the selection of the best alternative, and deploying tools to implement the design. We illustrate such use by surveying current industrial practice and introducing real world examples based on our practical experience in solving supply chain and reengineering problems.     

Decision support frameworks and metrics for sustainable development of minerals and metals

The Australian government-supported Co-operative Research Centre for Sustainable Resource Processing (CSRP) has undertaken a comprehensive review of sustainability metrics and decision support frameworks used by the global mining/minerals/metals sector. This paper provides a summary of that larger review. In particular, attention is given to the extent to which the plethora of current tools and approaches used by the industry are similar; the degree to which they conform with more formal approaches to decision making, as espoused by the management sciences community; and how indicators are, or should be, used to support decision making, or to set targets for achieving more sustainable outcomes from practices within the industry. We cite experience from six major companies within the sector as examples of current practice. Finally, we suggest how current best practice should be augmented by additional tools, which focus on information quality and management.     

Towards the derivation of an integrated process cost-modelling technique for complex manufacturing systems

Cost modelling is used to support business decisions, especially, when the objective is to remain competitive on price and be able to realise outputs at low cost. Many researchers and industrialists have proposed and experimented with different cost-modelling techniques with a view to influencing design and production decisions at an early stage of the development process. This has led to cost-modelling methods which have been broadly classified in this paper as qualitative and quantitative. The paper identifies current best practice cost-modelling techniques and their performance in complex and dynamic manufacturing environments. The review served as a platform to support the recommendation for an integrated cost-modelling methodology. The integrated methodology is based on the strengths of cost engineering, enterprise modelling, system dynamics and discrete event simulation modelling techniques. The method can help in the redesign and re-engineering of products and processes for better cost and value indications; support investment decision analysis; help determine appropriate business and manufacturing paradigms; influence ‘make, buy or outsourcing’ decisions and serve as a key process improvement tool.     

Applying the TOC thinking process in manufacturing: A case study

A case study is presented to illustrate the application of the Theory of Constraints thinking process logic tools in a manufacturing environment. The study firm performs design activities related to meeting future product requirements while concurrently meeting existing production schedules for the current design of the product. Current approaches to managing the firm's limited productive capacity do not allow for both design and production activities to occur simultaneously while meeting the customer's current product delivery schedule. Thus, despite their desire to satisfy their customer's future design requirements, management uses the majority of its production capacity to meet its customer's current product delivery schedule. This case study demonstrates how a team of employees used thinking process logic diagrams to document reality, identify a core conflict and problem, develop proposed changes to address the core problem, and create several detailed action plans to implement changes within the study organization. Initially, scenarios associated with some undesirable effects are used to understand how prevailing policies and behaviours result in less than desired production line performance. Then, a current reality tree is constructed to link the core problem or system constraint with the previously identified undesirable effects. Next, two major injections are developed to address the core problem in managing the production line as logically documented in a future reality tree. Finally, three transition trees are presented to guide the implementation of change at the study organization.     

Improving biomolecular pattern discovery and visualization with hybrid self-adaptive networks

There is an increasing need to develop powerful techniques to improve biomedical pattern discovery and visualization. This paper presents an automated approach, based on hybrid self-adaptive neural networks, to pattern identification and visualization for biomolecular data. The methods are tested on two datasets: leukemia expression data and DNA splice-junction sequences. Several supervised and unsupervised models are implemented and compared. A comprehensive evaluation study of some of their intrinsic mechanisms is presented. The results suggest that these tools may be useful to support biological knowledge discovery based on advanced classification and visualization tasks.     

A polychromatic sets approach to the conceptual design of machine tools

Currently very few computer-aided conceptual design systems are available to support the initial development of a machine tool and its structure (concept, calculation, design) and the verification of the prototype. In recent years, polychromatic sets have emerged as a promising approach for mathematical modelling. The theory, techniques, and approaches of polychromatic sets are capable of playing an important role in the conceptual design of a variety of products including machine tools. In this paper, the concept of polychromatic sets is introduced, and a polychromatic sets approach for the conceptual design of machine tools is proposed. The usefulness of the proposed method is illustrated by a conceptual design example of a machining centre of drilling, milling, and boring. Applying the proposed approach to machine tools helps to make right decisions in the conceptual design stage. Due to its powerful mathematical modelling capability, the polychromatic sets technique proposed in this paper may possibly be extended and applied to design evaluation problems encountered in other design tasks in manufacturing systems including process planning.     

An analytical approach to quantitative effect estimation of operation advisory system based on human cognitive process using the Bayesian belief network

The design of instrumentation and control (I&C) systems for nuclear power plants (NPPs) is rapidly moving towards fully digital I&C systems and is trending towards the introduction of modern computer techniques into the design of advanced main control rooms (MCRs) of NPPs. In the design of advanced MCRs, human–machine interfaces have improved and various types of decision support systems have been developed. It is important to design highly reliable decision support systems in order to adapt them in actual NPPs. In addition, to evaluate decision support systems in order to validate their efficiency is as important as to design highly reliable decision support systems. In this paper, an operation advisory system based on the human cognitive process is evaluated in order to estimate its effect. The Bayesian belief network model is used in the evaluation of the target system, and a model is constructed based on human reliability analysis event trees. In the evaluation results, a target system based on the operator's cognitive process showed better performance compared to independent decision support systems.     

Rapid one-of-a-kind product development via the Internet: a literature review of the state-of-the-art and a proposed platform

The historical background of Internet-based product design and manufacturing systems for rapid development of one-of-a-kind (OKP) products is systematically reviewed. By reviewing the existing OKP systems and recent approaches of Internet-based design and manufacturing systems, the requirements for the next generation of OKP systems and the current techniques that can be used to implement Internet-based product design and manufacturing systems for the rapid production of OKP products will be discussed. The problems that emerged from recent developments are reviewed and sorted. The future trends of Internet-based collaborative design, decision support, manufacturing support, supply chain management, workflow management, Internet techniques for product design and manufacturing, product modelling, STEP-based data environment, concurrent engineering, etc., will also be discussed. The reviewed state-of-the-art approaches are used directly or indirectly as references for the development of a new generation OKP systems. A reference system structure for building an Internet-based integrated product development system is then proposed to facilitate rapid development of OKP products.     

Enterprise integration engineering reference framework and toolbox

Enterprise Integration Engineering (EIE) has emerged as an engineering discipline to re-structure the enterprise entities as integrated business processes that integrate human and technological resources to facilitate the knowledge sharing for better decision making. EIE is a complex task that requires applying different tools concerning strategic planning, performance management, modelling, simulation and business process management in order to properly engineer the enterprise entities. The present paper presents an EIE toolbox that aims to support enterprises in their decision making process and to provide different assisting tools to be applied on the components of the EIE Reference Framework proposed. Finally, a set of case studies are presented in order to demonstrate the utility of the EIE Reference Framework and its toolbox for strategic planning and enterprise decision making.     

Problem identification in maintenance modelling: a case study

This paper is concerned with a problem identification and problem focus process in maintenance modelling. It endeavours to describe the process of moving from vague problem understanding towards more specific problem formulation and problem focus in the pursuit of practical decision making. This process was conducted using several analytical tools that complemented each other such as regression analyses, snapshot modelling and delay time modelling. As in many case studies related to maintenance modelling, this study also makes use of the experience of experts. It can be seen from the paper that subjective data estimates can prove to be a useful input for modelling. The analysis shows how simple modelling of maintenance problems can provide useful insights and better understanding of the problem in hand.     

On the representation of automation using a work domain analysis

Work domain analysis (WDA) has been applied extensively within cognitive engineering as an analytic framework for the evaluation of complex sociotechnical systems in support of design. However, the WDAs described in the literature have not explored the representation of automated system components, despite the documented problems associated with operator-automation interaction and the requirements for operator support in complex automated systems. The current research examines the application of WDA to model an example automated system – a camera – by representing the camera along with its automated components as separate systems using the abstraction hierarchy (AH). Additionally, we contrasted this modelling approach with the more typical approach of modelling automation within a cognitive work analysis (CWA) by performing a control task analysis using the decision ladder. The results of these analyses suggest that, similar to non-automated systems, considering a separate representation of an automated system within the WDA may provide useful system design guidance in terms of user support and information requirements. The comparison of the AH and the decision ladder (DL) models indicates that the models provide different information about the requirements and support different user needs: the AH provides information about specific subsystems and components of the automation that are used for control and how they support functions and purposes of the automation while the DL shows how the control tasks are achieved interleaving automated actions with those of the user. The information obtained from modelling automation with the AH is different from what would normally be obtained by performing only a control task analysis, yet is necessary for operator support.     

A disaster-severity assessment DSS comparative analysis

This paper aims to provide a comparative analysis of fuzzy rule-based systems and some standard statistical and other machine learning techniques in the context of the development of a decision support system (DSS) for the assessment of the severity of natural disasters. This DSS, which will be referred to as SEDD, has been proposed by the authors to help decision makers inside those Non-Governmental Organizations (NGOs) concerned with the design and implementation of international operations of humanitarian response to disasters. SEDD enables a relatively highly accurate and interpretable assessment on the consequences of almost every potential disaster scenario to be obtained through a set of easily accessible information about that disaster scenario and historical data about similar ones. Thus, although SEDD’s methodology is rather sophisticated, its data requirements are small, which, therefore, enables its use in the context of NGOs and countries requiring humanitarian aid. In this sense, SEDD opposes to some current tools which focuses on one phenomena-one place disaster scenarios (earthquakes in California, hurricanes in Florida, etc.) and/or have extensive and/or technologically sophisticated data requirements (real-time remote sensing information, exhaustive building census, etc.). Moreover, although focused on disaster response, SEDD can also be useful in other phases of disaster management, as disaster mitigation or preparedness. Particularly, the predictive accuracy and interpretability of SEDD fuzzy methodology is compared here in a disaster severity assessment context with those of multiple linear regression, linear discriminant analysis, classification trees and support vector machines. After an extensive validation over the EM-DAT disaster database, it is concluded that SEDD outperforms the methods above in the task of simultaneously providing an accurate and interpretable inference tool for the evaluation of the consequences of disasters.     

Strategies for planning experiments using orthogonal arrays and confounding tables

Genichi Taguchi has popularized a robust design method which employs experimental design techniques to help identify the levels of design factors to improve the quality of products and manufacturing processes. Experimental design techniques are extremely effective for identifying improved factor levels in problems that involve a large number of factors. Taguchi's success in getting engineers to use experimental design techniques is due, at least in large part, to his use of tools and techniques that simplify the experiment planning process. Recognizing the advantages of this approach, this paper proposes a new set of tools, confounding tables, which offer more guidance to experimenters. Confounding tables provide a clear and systematic representation of confounding relationships. They are simple and useful tools for constructing experiment plans, and they enable users easily to evaluate the confounding patterns of a completed plan. We show how confounding tables provide more information than Taguchi's linear graphs, and are useful for a large class of experiment plans.     

网络动态可视化的交互设计原则构建

目的构建网络动态可视化的交互设计原则。方法结合数据可视化基本设计方法分析网络数据可视化的设计案例,总结网络动态可视化的交互设计原则。结论网络动态可视化的设计过程中,应当遵循多数据元素分类显示、数据的分层显示、背景信息描述、交互视角管理、数据标记5项交互设计原则。构建可视化数据与用户之间的动态交互,将是网络数据可视化的焦点课题。     

Modelling reconfigurable manufacturing systems with coloured timed Petri nets

Reconfigurable manufacturing systems (RMSs) have been acknowledged as a promising means of providing manufacturing companies with the required production capacities and capabilities. This is accomplished through reconfiguring system elements over time for a diverse set of individualised products often required in small quantities and with short delivery lead times. Recognising the importance of dynamic modelling and visualisation in decision-making support in RMSs and the limitations of current research, we propose in this paper to model RMSs with Petri net (PN) techniques with focus on the process of reconfiguring system elements while considering constraints and system performance. In view of the modelling challenges, including variety handling, production variation accommodation, machine selection, and constraint satisfaction, we develop a new formalism of coloured timed PNs. In conjunction with coloured tokens and timing in coloured and timed PNs, we also define a reconfiguration mechanism to meet modelling challenges. An application case from an electronics company producing mobile phone vibration motors is presented. Also reported are system analysis and application results, which show how the proposed formalism can be used in the reconfiguration decision making process.     

Justification for the selection of manufacturing technologies: a fuzzy-decision-tree-based approach

In this paper, a developed model for the justification of alternative manufacturing technologies is presented. The approach, based on fuzzy decision trees, provides a methodology capable of identifying patterns within a technology case repository to support the evaluation of manufacturing systems. Experts are highly influential individuals in the decision process; they provide support and guidance when selecting investments. The experience-oriented task is founded on previous cases or an experts’ experience, and therefore difficult to express in a rational form. The concept is based on a number of characteristics of the case-based reasoning, rule induction and expert system theory. Structured around the fuzzy-decision-tree data-mining technique, the framework provides the ability of using regulated case information to act as structured experience for assisting in the decision process. Fuzzy induction extracts formal rules from a set of experience data, and the expert system philosophy computes the experience base of human expertise for problem-solving. A test case indicates the stability of the classification algorithm and verifies the applicability within the domain.