Engineering Deals Research Articles

BPRIM: An integrated framework for business process management and risk management

Enterprise engineering deals with the design of processes which aim to improve the structure and efficiency of business organizations. It develops approaches based on modeling techniques, particularly on business process modeling, to ensure the quality and the global consistency of enterprise strategies and expectations. Nowadays, risk consideration in enterprise engineering is a growing concern since the business environment is becoming more and more competitive, complex, and unpredictable. To face this concern, a paradigm named risk-aware business process management (R-BPM) has recently emerged. It seeks to integrate the two traditionally isolated fields of risk management and business process management. Despite the significant benefits that can arise from the use of R-BPM, it suffers from a lack of solid scientific foundations and dedicated tooling. This present research work contributes to bridging that gap in a twofold way: (i) by establishing the BPRIM Business Process-Risk Integrated Method framework, and (ii) by designing a dedicated tool, named adoBPRIM which supports the efficient application of the BPRIM framework. This paper first comprehensively presents the foundation of BPRIM which is based on three main components and, secondly, its dedicated tool adoBPRIM which was designed using the ADOxx meta-modeling platform. An evaluation with a real case study in the health care domain shows the relevance of the methodological framework.

Aspect Based Sentiment Analysis of Ridesharing Platform Reviews for Kansei Engineering

At present online reviews are becoming an important source for Kansei engineering of the services provided by ridesharing platforms. Kansei engineering deals with incorporating customer feedback and demands into product and service design. Thus, it is used as a tool for organizations to uplift their businesses by considering customer reviews and feedback. Customer reviews available on social media are in unstructured form; therefore, sentiment analysis is employed to extract customer’s opinions in a systematic manner. In India-Pakistan, these reviews are mostly in Roman Urdu/Hindi and English, which are of great value for ridesharing platforms as a part of their Kansei engineering strategy. However, sentiment analysis cannot be performed directly on these reviews as they are mostly in Roman Urdu/Hindi. Therefore, the objective of this paper is to conduct aspect based sentiment analysis on these reviews after translating them into English for Kansei engineering of the service. Consequently, sentiment analysis is carried out to extract the most frequent features along with nouns and adjectives used by the customers to express their sentiments. We extracted prominent aspects of the service (i.e., ‘Driver’, ‘Company’, ‘Service’, and ‘Ride’) based on their highest frequencies using aspect based sentiment analysis. The customer sentiments are then clustered into these main aspects using unsupervised machine learning technique. Each aspect is further analyzed based on their polarity, which serves as an input for Kansei engineering of the service. As a result, it can facilitate ridesharing companies to enhance their businesses by improving services in accordance with customer demands.

Optimization on machining parameters of friction surfacing of SS304 over iron plate

Surface engineering deals with the surface of the material and it was sub-discipline of materials science. Wear can be reduced by modifying the surface properties of solids by coating hard material or by use of lubricants. Friction surfacing is one of the surface coating method which gives better bonding on plane surfaces. In this work, iron plate was taken as substrate and stainless steel (SS) 304 was used as coating material. The experiment was conducted based on L9 orthogonal array. The parameters chosen for the experiment were rotational speed, axial load and traverse speed. The response values were hardness and maximum displacement in order to improve the wear, corrosion and bonding strength. The results were analyzed using Taguchi method to find the optimum machining parameters and to identify the effect of machining parameter for maximum hardness and displacement. ANOVA was employed to confirm the result obtained from Taguchi method. ANOVA was also used to identify the contribution percentage of each parameters.

BPRIM: An integrated framework for business process management and risk management

Enterprise engineering deals with the design of processes which aim to improve the structure and efficiency of business organizations. It develops approaches based on modeling techniques, particularly on business process modeling, to ensure the quality and the global consistency of enterprise strategies and expectations. Nowadays, risk consideration in enterprise engineering is a growing concern since the business environment is becoming more and more competitive, complex, and unpredictable. To face this concern, a paradigm named risk-aware business process management (R-BPM) has recently emerged. It seeks to integrate the two traditionally isolated fields of risk management and business process management. Despite the significant benefits that can arise from the use of R-BPM, it suffers from a lack of solid scientific foundations and dedicated tooling. This present research work contributes to bridging that gap in a twofold way: (i) by establishing the BPRIM business process-risk integrated method framework, and (ii) by designing a dedicated tool, named adoBPRIM which supports the efficient application of the BPRIM framework. This paper first comprehensively presents the foundation of BPRIM which is based on three main components and, secondly, its dedicated tool adoBPRIM which was designed using the ADOxx meta-modeling platform. An evaluation with a real case study in the health care domain shows the relevance of the methodological framework.

Swirling fluid flow in flexible, expandable elastic tubes: Variational approach, reductions and integrability

Many engineering and physiological applications deal with situations when a fluid is moving in flexible tubes with elastic walls. In real-life applications like blood flow, a swirl in the fluid often plays an important role, presenting an additional complexity not described by previous theoretical models. We present a theory for the dynamics of the interaction between elastic tubes and swirling fluid flow. The equations are derived using a variational principle, with the incompressibility constraint of the fluid giving rise to a pressure-like term. In order to connect this work with the previous literature, we consider the case of inextensible and unshearable tube with a straight centerline. In the absence of vorticity, our model reduces to previous models considered in the literature, yielding the equations of conservation of fluid momentum, wall momentum and the fluid volume. We pay special attention to the case when the vorticity is present but kept at a constant value. We show the conservation of energy-like quality and find an additional momentum-like conserved quantity. Next, we develop an alternative formulation, reducing the system of three conservation equations to a single compact equation for the back-to-labels map. That single equation shows interesting instability in solutions when the velocity exceeds a critical value. Furthermore, the equation in stable regime can be reduced to Boussinesq-type, KdV and Monge–Ampère equations in several appropriate limits, namely, the first two in the limit of a long time and length scales and the third one in the additional limit of the small cross-sectional area. For the unstable regime, the numerical solutions demonstrate the spontaneous appearance of large oscillations in the cross-sectional area.

Practical Experiences in the Use of Pattern-Recognition Strategies to Transform Software Project Plans into Software Business Processes of Information Technology Companies

Business process management (BPM) is a strategic advantage for all kinds of organizations, including information technology companies (ITCs), which cannot stay out of the BPM approach. ITCs manage business processes like projects to create and maintain software. Although Project Management Systems (PMSs), such as Microsoft™ Project Server® (MPS®), are considered as non-process-aware information systems (Non-PAISs), they may be a source to generate processes. In this paper, we propose a reverse engineering approach, which uses patterns to transform software projects stored in MPS® legacy databases into software business processes. For this, we base on the model-driven engineering paradigm and deal with the time perspective of the processes. This kind of experiences are scarce or almost nonexistent, so we show the AQUA-WS project case study, which runs with MPS® as source system and software process modeling languages as target systems. ITCs can benefit from this research by gathering knowledge about perspectives of their processes that would otherwise be wasted, such as executed projects or expired documents used in Non-PAISs. This fact can become a key factor for ITCs, which can increase their competitiveness and reduce software costs, as part of the BPM lifecycle of continuous improvement.

Directed assembly of active colloidal molecules

Having a production line for microrobots is fundamental to their widespread application in many areas. Thanks to their flexibility, active colloidal molecules with dynamic function are a promising model for microrobots. So far, the production of colloidal molecules requires a great deal of engineering and ad hoc processes. Here, we first describe a method for the continuous production of dimers and trimers formed by non-polar spherical active colloidal particles. We use external fields to both guide the monomers and rotate the colloidal molecules as to obtain dimers and trimers with very high yield and highly localized in space. We also show how fields and rigid walls can be used to direct small colloidal molecules to specific locations. Finally, we study the possible colloidal molecules that can be created with these building blocks and propose a general mechanism for the directed assembly of colloidal molecules with dynamic function.

Enhancing theWeb WithAdvanced Engineering

Enhancing theWeb WithAdvanced Engineering

Model-based training of manual procedures in automated production systems

Maintenance engineers deal with increasingly complex automated production systems, characterized by increasing computerization or the addition of robots that collaborate with human workers. The effects of changing or replacing components are difficult to assess since there are complex interdependencies between process parameters and components. The introduction of models that describe such dependencies into training systems could support the understanding of these interdependencies and the formation of a correct mental model of a maintenance procedure and the machine and thereby improve the training success. This paper proposes a model-based training system that introduces domain-independent SysML models that formalize such dependencies. The training system consists of a virtual training system for initial training and an online support system for assistance during the procedures. The on- and offline training systems visualize the state of the machine at a certain step of the procedure using structural SysML models. An evaluation of the system against a paper-based manual validated the motivations and showed promising results regarding effectiveness, usability and attractiveness.

Nutrient transport through deformable cylindrical scaffold inside a bioreactor: An application to tissue engineering

Tissue engineering deals with the development and growth of cells to obtain tissue structure or organs. In this process, a porous material known as a scaffold is designed to support the cells to grow in the desired form. This designed structure is incubated inside a bioreactor which provides adequate nutrient supply for the cells to grow. The major challenge in tissue engineering is to model a bioreactor and the scaffold which supports high-density cells so that adequate nutrient can be delivered in inner regions to get the significant cell growth. Mathematical modeling of such processes is essential to understand the entire mechanism. Correspondingly, a mathematical model for fluid flow and nutrient transport is developed inside a cylindrical bioreactor containing tubular scaffold which is degradable as well as deformable due to its elastic property. Living biological cells are assumed to adhere to the solid matrix of scaffold firmly. The volume fraction of the solid phase which includes cells and scaffold matrix is assumed to be constant despite the fact that proliferation of cells and degradation of scaffold matrix are undergoing simultaneously. Fluid flow and deformation of the tissue (scaffold) are modeled based on biphasic mixture theory. Navier–Stokes equation accounts for the free fluid in the annular region of the bioreactor. Advection–diffusion-reaction equation governs the concentration of a nutrient in the scaffold region whereas advection–diffusion equation governs the nutrients in the free lumen. Semi-analytical treatment on the mathematical model includes Laplace transformation to deal with the time dependency of the governing fluid flow equation and consequently, Durbin’s algorithm is used to retrieve the time-dependent variables. The model allows the uniform nutrient transport inside the scaffold region so that cells get sufficient amount of nutrient to grow and reduce the cell death. Moreover, Sherwood number has been calculated to analyse the mass transport of solute concentration from scaffold region to the free fluid region and vice-versa through the interface.

Design of Advanced Control Strategies for Cardiovascular System

Cardiovascular diseases are chief causes of anguish and mortality in the developed countries. Bio-medical engineering deals with the application of various approaches of engineering in the field of medicine and biology mainly for health care purposes thereby improving patient’s quality of life. Out of the various techniques, the important focus is to develop a reliable and optimized technique for simulation of electric activity of heart. In an effort to make such a technique this work describes the design of a control system for regulating the Heart Rate (HR) for pacemaker in an efficient way. The overall control system to be developed, in this work is considered to be composed of cardiovascular system duly triggered by an intelligent pacemaker system as operated in a closed loop manner with unity negative gain in the feedback path. A conventional controller based on Proportional, Integral and Derivative (PID) is designed with the help of Zeigler-Nichols, Neural controller and Adaptive control schemes. The simulations have been carried out using MATLAB/SIMULINK. By the way of comparative study of simulated results of different control techniques it is found that the overall response of adaptive controller is better than the conventional PID controller.

The knowledge graph as the default data model for learning on heterogeneous knowledge

In modern machine learning, raw data is the pre-ferred input for our models. Where a decade ago data scien-tists were still engineering features, manually picking out the details they thought salient, they now prefer the data in their raw form. As long as we can assume that all relevant and ir-relevant information is present in the input data, we can de-sign deep models that build up intermediate representations to sift out relevant features. However, these models are often domain specific and tailored to the task at hand, and therefore unsuited for learning on heterogeneous knowledge: informa-tion of different types and from different domains. If we can develop methods that operate on this form of knowledge, we can dispense with a great deal of ad-hoc feature engineering and train deep models end-to-end in many more domains. To accomplish this, we first need a data model capable of ex-pressing heterogeneous knowledge naturally in various do-mains, in as usable a form as possible, and satisfying as many use cases as possible. In this position paper, we argue that the knowledge graph is a suitable candidate for this data model. This paper describes current research and discusses some of the promises and challenges of this approach.

Complexity of Curved Glass Structures

Despite the increasing number of research on the architectural structures of curvilinear forms and technological and practical improvement of the glass production observed over recent years, there is still a lack of comprehensive codes and standards, recommendations and experience data linked to real-life curved glass structures applications regarding design, manufacture, use, performance and economy. However, more and more complex buildings and structures with the large areas of glass envelope geometrically complex shape are built every year. The aim of the presented research is to collect data on the existing design philosophy on curved glass structure cases. The investigation includes a survey about how architects and engineers deal with different design aspects of curved glass structures with a special focus on the design and construction process, glass types and structural and fixing systems. The current paper gives a brief overview of the survey findings.

Silk Protein based Novel Matrix for Tissue Engineering Applications

Tissue engineering deals with recreating, maintaining and enhancing the damaged or lost tissue/organ of living organisms. For tissue engineering applications, biomaterials are needed, that can be derived from either natural or synthetic source. Silk is one of the best natural biomaterials because of its properties like biocompatibility, high mechanical strength and slow degradation rate in vivo. Present study describes the synthesis of silk fibroin hydrogel using photopolymerization method. Aqueous silk fibroin solution was blended with synthetic polymer. The solution was then exposed by a monochromatic light source for the polymerization process. During the polymerization process, sample was at a specific distance from the light source under controlled temperature conditions i.e; at 37⁰C. After the incubation period of around 3 hours, matrix with soft, slippery and elastic surface was obtained. The matrix obtained can further be used as a source for drug delivery carrier, for sustained delivery of drug, in the field of gene therapy for controlled release of DNA at the targeting site and also be used for bone and cartilage tissue engineering.

Incorporating decision maker\u2019s preferences in a multi-objective approach for the software release planning

BackgroundRelease planning (RP) is one of the most complex and relevant activities in the iterative and incremental software development, because it addresses all decisions associated with the selection and assignment of requirements to releases. There are many approaches in which RP is formalized as an optimization problem. In this context, search-based software engineering (SBSE) deals with the application of search techniques to solve complex problems of software engineering. Since RP is a wicked problem with a large focus on human intuition, the decision maker’s (DM) opinion is a relevant issue to be considered when solving release planning problem. Thus, we emphasize the importance in gathering the DM’s preferences to guide the optimization process through search space area of his/her interests.MethodsTypically, RP is modelled as a multi-objective problem by considering to maximize overall clients satisfaction and minimize project risk. In this paper, we extend this notion and consider DM’s preferences as an additional objective. The DM defines a set of preferences about the requirements allocation which is stored in a preference base responsible for influencing the search process. The approach was validated through an empirical study, which consists of two different experiments, respectively identified as (a) automatic experiment and (b) participant-based experiment. Basically, the former aims to analyze the approach using different search-based algorithms (NSGA-II, MOCell, IBEA, and SPEA-II), over artificial and real-world instances, whereas the latter aims at evaluating the use of the proposal in a real scenario composed of human evaluations.ResultsThe automatic experiment points out that NSGA-II obtained overall superiority in two of the three datasets investigated, positioning itself as a superior search technique for scenarios with few number of requirements and preferences, while IBEA showed to be better for larger ones (with more requirements and preferences). Regarding the participant-based experiment, it was found that two thirds of the participants evaluated the preference-based solution better than the non-preference-based one.ConclusionsThe results suggest that it is feasible to investigate the approach in a real-world scenario. In addition, we made available a prototype tool in order to incorporate the human’s preferences about the requirements allocation into the solution of release planning.

Kalman: The Scientist Who Defined Our Field [Historical Perspectives

Until about 1960, systems and control were identified with input/output thinking. This was the dominant, if not the unique, point of view from which control problems were approached, at least in the Western literature. In the early 1960s, new fundamental concepts introduced by Kalman precipitated what has been later dubbed a big bang in systems theory. Concepts such as controllability, observability [1], optimal control [2], and state estimation [3] have deeply changed the way in which scientists and engineers deal with control problems.

Experimental and numerical approaches for the quantification of tumble intensity in high-performance SI engines

The activity presented in the paper is focused on the development of a high-performance engine specifically dedicated to CNG fueling. The engine features a variable valve actuation system as well as different possible compression ratios ranging between 12 and 14. More specifically, the present work carries out an experimental and numerical characterization of the steady-state tumble flow from the engine head and deals with the development and assessment of a numerical model for the engine-cycle transient simulation. Experimental tests were carried out at Fiat Research Center (CRF) on a flow test rig equipped with two different devices for the tumble measurement, based on the Ricardo method and on the two-dimensional HWA acquisition of the axial velocity, respectively. It is worth highlighting that the HWA technique was purposely developed by CRF for the tumble characterization. The experimental results were also used for the calibration of a ‘virtual flow box’ numerical model, which was in turn exploited to gain complimentary information about the characteristics of the tumbling flow and to define the requirements for the transient CFD model of the real engine, both in terms of discretization mesh and turbulence modeling.The results showed that the HWA technique represents a factual alternative to the integral techniques for tumble characterization. It also provides additional information about the unevenness of the flow distribution generated by the intake system. The ‘virtual flow box’ simulations pointed out that good results can be obtained by using the Realizable k-ε model, whereas both the Realizable and the RNG k-ε models proved to be appropriate for the engine transient simulations. Finally, the CFD models showed to be fairly accurate and reliable, especially when the relative changes from one engine geometry and/or valve actuation to another need to be accounted for.

Performance Analysis of a Helium Turbo-expander for Cryogenic Applications with a Process Modeling Tool: Aspen HYSYS

Cryogenic system refers to interacting group of components involving low temperature. Cryogenic engineering deals with the development and improvement of low temperature techniques, processes, and equipment. They are applicable to helium refrigerators and various liquefiers. Nowadays, the energy crisis has forced the need to recover the energy which is normally wasted in other industrial processes. Reduction of gas pressure is one of such process in which there is a high loss of energy. To prevent such high wastage of energy, Turbo-expander which is the heart for the production of low temperature by reducing the pressure to a low value, has been introduced in the industries. Turbo-expanders are used in almost every segments of the oil and gas industry to produce Cryogenic refrigeration. Before implementation of such a critical component in the plant, it is necessary to carry out the performance analysis of turbo-expander. In this paper, a process simulator called Aspen HYSYS is used for the analysis of Helium turbo-expander (Helium gas is taken as a process sample gas) and detailed observation is carried out for checking the performance of helium turbo-expander at various adiabatic efficiencies. The results provide useful indications on the selection of turboexpander to obtain required output at various efficiencies with variation in temperature. Keeping the constraints of the plant in mind, this analysis can thus result in the design of an efficient productive plant

Improving the Productivity of Industrial Systems: A Simulation-Based Case Study

The modern Industrial Engineering deals with complex engineering systems which require a holistic approach to reinforce their efficiency, flexibility, and sustainability. Deliver high-quality customized products is mandatory while maintaining high levels of productivity so, the operations managers are continuously evaluating their systems in order to improve them. These improvements are usually action based and rely on decision processes with inherent trade-offs. So, methods and tools to support these decision-making processes are essential to operations managers in order to help them to choose the best course of action. This paper reports a real-world industry case study illustrating the advantages of using simulation to analyze the current systems and to evaluate different scenarios regarding productivity improvements.

Plasmonically Engineered Nanoprobes for Biomedical Applications.

The localized surface plasmon resonance of metal nanoparticles is the collective oscillation of electrons on particle surface, induced by incident light, and is a particle composition-, morphology-, and coupling-dependent property. Plasmonic engineering deals with highly precise formation of the targeted nanostructures with targeted plasmonic properties (e.g., electromagnetic field distribution and enhancement) via controlled synthetic, assembling, and atomic/molecular tuning strategies. These plasmonically engineered nanoprobes (PENs) have a variety of unique and beneficial physical, chemical, and biological properties, including optical signal enhancement, catalytic, and local temperature-tuning photothermal properties. In particular, for biomedical applications, there are many useful properties from PENs including LSPR-based sensing, surface-enhanced Raman scattering, metal-enhanced fluorescence, dark-field light-scattering, metal-mediated fluorescence resonance energy transfer, photothermal effect, photodynamic effect, photoacoustic effect, and plasmon-induced circular dichroism. These properties can be utilized for the development of new biotechnologies and biosensing, bioimaging, therapeutic, and theranostic applications in medicine. This Perspective introduces the concept of plasmonic engineering in designing and synthesizing PENs for biomedical applications, gives recent examples of biomedically functional PENs, and discusses the issues and future prospects of PENs for practical applications in bioscience, biotechnology, and medicine.