Complex Product Structures Research Articles

Ontological model of structure and parameters of components in high-tech product modernization projects

The subject of the article is models representing the structure and parameters of components in high-tech products based on the analysis of technical documentation in modernization projects. The purpose of the proposed research is to enhance the quality of modernization processes of high-tech products by forming an ontological model of the product with innovative components, considering the diversity of information support. The article addresses the following tasks: studying the main methods and technologies of system representation of complex product structure; forming a model of structural-functional decomposition of a high-tech product, creating an ontological model of the structure and parameters of a high-tech product based on technical documentation. The following methods are applied: systemic approach, methods of functional-structural decomposition, set theory, ontology construction methods, semantic models. The following results were obtained: The main methods of system representation of complex product structure were investigated, based on the following principles: decomposition of complex product architecture, layering of complex product representation, multivariate synthesis of component architecture. The main directions and advantages of using 3D technologies for solving design tasks in modernization projects of high-tech product components are considered. The decomposition of a high-tech product into component parts and partial parameters is proposed, taking into account functional, structural, and parametric characteristics. An ontological model of the structure and parameters of a high-tech product is formed based on a set of technical documentation and considering additional heterogeneous sources of information. Innovative elements are identified, the description of which may be fuzzy. Conclusions. The proposed ontological model can serve as a basis for finding similar solutions regarding the design of innovative components in the precedent database, which is properly structured. In the absence of similar design solutions, innovative component design can be carried out using 3D technologies based on supplementing fuzzy information in the semantic model.

Symplectic structures, product structures and complex structures on Leibniz algebras

In this paper, a symplectic structure on a Leibniz algebra is defined to be a symmetric nondegenerate bilinear form satisfying certain compatibility condition, and a phase space of a Leibniz algebra is defined to be a symplectic Leibniz algebra satisfying certain conditions. We show that a Leibniz algebra has a phase space if and only if there is a compatible Leibniz-dendriform algebra, and phase spaces of Leibniz algebras are one-to-one corresponds to Manin triples of Leibniz-dendriform algebras. Product (paracomplex) structures and complex structures on Leibniz algebras are studied in terms of decompositions of Leibniz algebras. A para-Kähler structure on a Leibniz algebra is defined to be a symplectic structure and a paracomplex structure satisfying a compatibility condition. We show that a symplectic Leibniz algebra admits a para-Kähler structure if and only if the Leibniz algebra is the direct sum of two Lagrangian subalgebras as vector spaces. A complex product structure on a Leibniz algebra consists of a complex structure and a product structure satisfying a compatibility condition. A pseudo-Kähler structure on a Leibniz algebra is defined to be a symplectic structure and a complex structure satisfying a compatibility condition. Various properties and relations of complex product structures and pseudo-Kähler structures are studied. In particular, Leibniz-dendriform algebras give rise to complex product structures and pseudo-Kähler structures naturally.

Para-Kähler and pseudo-Kähler structures on Lie–Yamaguti algebras

For a pre-Lie–Yamaguti algebra [Formula: see text], by using its sub-adjacent Lie–Yamaguti algebra [Formula: see text], we are able to construct a semidirect product Lie–Yamaguti algebra via a representation of [Formula: see text]. The investigation of such semidirect Lie–Yamaguti algebras leads us to the notions of para-Kähler structures and pseudo-Kähler structures on Lie–Yamaguti algebras, and also gives the definition of complex product structures on Lie–Yamaguti algebras. Furthermore, a Levi–Civita product with respect to a pseudo-Riemannian Lie–Yamaguti algebra is introduced and we explore its relation with pre-Lie–Yamaguti algebras.

Life Cycle Assessment of a Jet Printing and Dispensing Machine

Life Cycle Assessment (LCA) is a well-known methodology used to calculate the environmental impacts of a product across its life cycle. The industrial machines used to manufacture consumer products are generally heavy, bulky, and have a complex product structure which makes their environmental assessment using LCA difficult as well as time and resource-intensive. Few studies have conducted LCA of complex industrial machines. The paper presents an LCA of a jet printing and dispensing machine (MY700), an industrial machine used in the production of printed circuit boards (PCBs) carried out using ReCiPe 2016 (Hierarchist) impact assessment methodology. In this study, the use phase of the machine accounted for 91% of the total environmental impacts. The compressed air and electricity consumed in the use phase of the machine were the major environmental hotspots. Additionally, some measures to minimize energy and compressed air use are also discussed. The methodology proposed in this article can be adopted by practitioners to conduct LCA of other industrial machines. The results of this study can help the machine manufacturers to undertake relevant eco-design activities as well as a comparison of different versions/machines in the product family for their environmental impact.

Modelling the Reliability of Logistics Flows in a Complex Production System

This paper analyses the disruptions occurring in a production system determining the operating states of a single machine. A system with a convergent production character, in which both single flows (streams) and multi-stream flows occur, was considered. In this paper, a two-level formalisation of the production system (PS) was made according to complex systems theory. The continuity analysis was performed at the operational level (manufacturing machine level). The definition of the kth survival value and the quasi-coherence property defined on chains of synchronous relations were used to determine the impact of interruption of the processed material flow on uninterrupted machine operation. The developed methodology is presented in terms of shaping the energy efficiency of technical objects with the highest power demand (the furnace of an automatic paint shop and the furnace of a glass tempering line were taken into consideration). The proposed methodology is used to optimise energy consumption in complex production structures. The model presented is utilitarian in nature—it can be applied to any technical system where there is randomness of task execution times and randomness of unplanned events. This paper considers the case in which two mutually independent random variables determining the duration of correct operation TP and the duration of breakdown TB are determined by a given distribution: Gaussian and Gamma family distributions (including combinations of exponential and Erlang distributions). A formalised methodology is also developed to determine the stability of system operation, as well as to assess the potential risk for arbitrary system evaluation parameters.

Pyrolysis-Free Synthesis of Bimetal Phthalocyanine Covalent Organic Polymers/Ordered Mesoporous Carbon Nanocomposites for an Efficient Oxygen Reduction Reaction

The development of non-noble metal–nitrogen ring complex (M–N–C) catalysts with high activity and stability for the oxygen reduction reaction (ORR) is of great significance. However, M–N–C catalysts are generally prepared from precursors under high-temperature pyrolysis, which leads to complex product structures and makes it difficult to identify the catalytic active center. Herein, we have successfully structured a novel bimetal phthalocyanine covalent organic polymer/ordered mesoporous carbon (CoFe-COP/OMC) electrocatalyst through a pyrolysis-free approach. Due to the well-defined active sites (Fe/CoN4), ordered COP structure, and highly conductive carrier materials, the CoFe-COP/OMC nanocomposite exhibits remarkable ORR electrocatalytic activity with a half-wave potential and initial potential of 0.908 and 0.932 V (vs reversible hydrogen electrode (RHE)), respectively, a limiting current density of 5.35 mA cm–2, and a nearly four-electron reduction pathway. In addition, the acquired hybrid catalysts show excellent methanol resistance and electrochemical stability compared with Pt/C. The outstanding performance confirms that the CoFe-COP/OMC nanocomposite is a promising high-efficiency ORR catalyst for metal–air batteries and fuel cells.

Lagrangian and orthogonal splittings, quasitriangular Lie bialgebras, and almost complex product structures

We study complex product structures on quadratic vector spaces and on quadratic Lie algebras analyzing the Lagrangian and orthogonal splittings associated with them. We show that a Manin triple equipped with generalized metric G+B such that B is an O-operator with extension G of mass −1 can be turned into another Manin triple that admits also an orthogonal splitting in Lie ideals. Conversely, a quadratic Lie algebra orthogonal direct sum of a pair of anti-isomorphic Lie algebras, following similar steps as in the previous case, can be turned into a Manin triple admitting an orthogonal splitting into Lie ideals.

Turning Sorrow into Treasured Gold: Airline Complexity and Responses to the Covid Pandemic

When firms face sudden and unusual crises, decision-makers need to quickly respond, and these responses have short-term costs and benefits but can also have long-term consequences that alter the strategy. A question of long-standing interest is whether firms with complex assets and production structures will respond slowly because the complexity delays understanding of the best response and reduces ability to implement it. The airline industry responses to the Covid pandemic are ideal for testing this proposition because the industry experienced rapid and sizable reductions in demand, and airlines differ significantly in complexity along easily measurable dimensions. The analysis demonstrates how airline decisions to store, retire, or sell aircraft differed in response to increased state policy stringency as a function of their complexity.

Quantum-inspired degradation modeling and reliability evaluation of battery management system for electric vehicles

The battery management system (BMS) is vital to the condition monitoring and charging-discharging control of battery packs in electric vehicles. Its reliability is highly concerned and degradation tests are generally conducted to evaluate the long-term reliability of this kind of highly reliable systems. As the result of increasingly complex product structure and the environmental impact, the degradation behavior of BMS would show unbalanced and heterogeneous characteristics. The usual approaches with unimodal degradation amount distribution could not correctly model the phenomenon. This paper presents a novel quantum-inspired degradation model to account for the two-cluster degradation trend of electronic devices. The deterioration of performance is modeled based on the interaction between the system and surroundings, with the discrete-time quantum walk describing the reduced dynamics of the system. The degradation dataset of a BMS is used to verify the validity and superiority of the proposed method. In general, this paper provides an alternative approach to the degradation modeling and reliability assessment of complex electronic devices. It explores future research direction with the understanding of reliability science.

A Two-Level Optimization Approach For Engineer-To-Order Project Scheduling*

This paper presents a new formulation of the flexible job-shop scheduling problem with outsourcing options adapted for Engineer-To-Order (ETO) products. Our formulation enables modeling complex product structures with flexible precedence relations between elements and operations. Having a significant role in the ETO context, the specificity of non-physical operations (design and engineering) is taken into account. Indeed, non-physical operations are subject to a validation stage, can be iterated in case of non-validation, and are executed once for several identical elements. The proposed approach is governed by a new ETO strategy to overcome the impact of the design uncertainty and element cancellations (time and financial wastes). First, the production and purchase of the most uncertain elements are delayed at the latest while their design is validated early. Besides, in the presence of similar elements, an element can be saved when cancelled by being used as a sub-part of another one. The proposed approach sequentially solves two mathematical models. The first model aims to minimise the makespan and outsourcing costs. The second model maximizes the solution robustness and the ability of saving elements while being governed by the completion time and project cost, output of the first model. The obtained results and a comparative study show the efficiency and robustness of the proposal.

A New Multi Echelon Repair Network Model with Multiple Upstream Locations for Level of Repair Analysis Problem

Level of repair analysis (LORA) determines (1) the best decision during a malfunction of each product component; (2) the location in the repair network to perform the decision and (3) the quantity of required resources in each facility. Capital goods have long life cycles and their total life cycle costs are extremely high. LORA, which can be done repeatedly during the life cycle of the product, both at design and product support phase, plays an important role in minimising the total life cycle costs of capital goods. It is mostly applied to systems that operate in different geographical areas and deployed in different regions, which include different subsystems with special technology and expertise, and have a complex product structure. In this study, we propose a new mathematical model to the LORA problem, which is more comprehensive and flexible than the other pure LORA models in the literature. The proposed model uses the multiple upstream approach that allows the transfer of the components from a location in the lower echelon to the predefined locations in the upper echelon and determines the material movement paths between each facility, defining the facilities’ locations in the repair network. The performance of the proposed model is tested on benchmark instances and the results are compared with the single upstream model. Computational experiments show that the proposed model is more effective than the single upstream model and reduces the total life cycle costs by 4.85% on average, which is an enormous cost saving when total life cycle costs of capital goods are considered.

Assembly of polyfunctional arenes with three contiguous and different substituents by Pd-catalyzed four-component reactions

The innovation of versatile multi-component reaction modes for one-pot assembly of polyfunctional arenes is a highly challenging and important goal in organic synthesis. Here, we report that polyfunctional arenes with three contiguous and different substituents can be assembled efficiently under mild conditions in a one-pot, four-component modular way by orchestrating mechanistically sequential and compatible palladium-catalyzed domino carbopalladation of arynes and norbornene (NBE)-mediated Catellani processes. Optimization of the reaction conditions reveals that balancing the reaction parameters in general, and loading amount of NBE especially, is a linchpin for the reaction. Studies of the reaction scope indicate a wide selection of functional groups, including complex natural product-derived substructures, can be tolerated, making it appealing for early- and late-stage assemblies. Post-transformations show that not only the newly installed substituents but also the parent aromatic nucleus can be derived conveniently, enabling polyfunctional arenes with diverse substitutions in a concise manner. General one-pot, four-component modular domino synthesis Three contiguous and different substituents Benzenes with up to six substituents Shen et al. describe a general, palladium-catalyzed, four-component reaction that can incorporate different functional groups onto three successive positions of benzene rings. The reaction tolerates complex natural product structures, and the products can be derived diversely.

A big data-driven root cause analysis system: Application of Machine Learning in quality problem solving

Root cause analysis for quality problem solving is critical to improve product quality performance and reduce the quality risk for manufacturers. Subjective conventional methods have been applied frequently in past decades. However, due to increasingly complex product and supply chain structures, diverse working conditions, and massive amounts of components, accuracy and efficiency of root cause analysis are progressively challenged in practice. Therefore, data-driven root cause analysis methods have attracted attention lately. In this paper, taking advantage of the availability of big operations data and the rapid development of data science, we design a big data-driven root cause analysis system utilizing Machine Learning techniques to improve the performance of root cause analysis. More specifically, we first propose a conceptual framework of the big data-driven root cause analysis system including three modules of Problem Identification, Root Cause Identification, and Permanent Corrective Action. Furthermore, in the Problem Identification Module, we construct a unified feature-based approach to describe multiple and different types of quality problems by applying a data mining method. In the Root Cause Identification Module, we use supervised Machine Learning (classification) methods to automatically predict the root causes of multiple quality problems. Finally, we illustrate the accuracy and efficiency of the proposed system and algorithms based on actual quality data from a case company. This study contributes to the literature from the following aspects: (i) the integrated system and algorithms can be used directly to develop a computer application to manage and solve quality problems with high concurrences and complexities in any manufacturing process; (ii) a general procedure and method are provided to formulate and describe a large quantity and different types of quality problems; (iii) compared with traditional methods, it is demonstrated using real case data that manufacturing companies can save significant time and cost with our proposed data-driven root cause analysis system; (iv) this study not only aims at improving the quality problem solving practices for a complex manufacturing process but also bridges a gap between the theoretical development of Machining Learning methods and their application in the operations management domain.

Economía afectiva y prosumidores: elementos para el abordaje de la cocreación en las industrias creativas colombianas

Las industrias creativas atraviesan por importantes cambios debido a constantes desarrollos tecnológicos y a la creación de proyectos con complejas estructuras de producción que han propiciado el surgimiento del prosumidor. Este renovado actor de la producción cultural se ha vinculado a distintas iniciativas de creación aportando recursos económicos o conocimiento. Las iniciativas de creación colaborativa toman el nombre de cocreación y generan el replanteamiento de diversas facetas de la producción. Para indagar sobre este fenómeno se han revisado los postulados teóricos desarrollados en la última década acerca de la cocreación, el transmedia y el prosumidor. En el rastreo se identificó la falta de una definición clara de cocreación, la cual se debe a que los investigadores han abordado el tema de forma fragmentada, lo que imposibilita una visión completa del fenómeno. En el estudio se propone una definición concreta de cocreación, que integra a todos los elementos que la condicionan. Asimismo, se señala un camino metodológico para el desarrollo de este tipo de prácticas en las industrias creativas colombianas.

Application of FTA-PCR technology combined with LIMS system in food safety inspection

With the increasing awareness of public health in the world, traditional food safety testing technology can no longer meet the needs of increasingly complex food types and product structures. The combination of traditional testing and biotechnology is a new force in strengthening food protection testing technology. This article analyzes the FTA-PCR technology combined with the LIMS system, based on the traditional chemical food safety testing, combined with the effective application of biotechnology in food safety testing, and explained the FTA-PCR technology combined with the LIMS system for food safety testing. In order to provide some help for the better development of my country’s new food safety testing technology.

Sustainable part consolidation model for customized products in closed-loop supply chain with additive manufacturing hub

Abstract In recent years, additive manufacturing (AM) has gained considerable interest because of its capacity to facilitate the fabrication of products of various shapes better than conventional manufacturing (CM). Moreover, it can respond to the growing demand for customized products and can reduce the impact on the environment by minimizing production waste. To maximize these benefits and overcome entry barriers, researchers have conducted part consolidation (PC) research to improve sustainability by reducing the number of components, or hybrid supply chain studies involving local AM service providers. This study aims to present a new supply chain that combines the advantages of both AM and CM systems to create and analyze the potential of an AM machine that can be made available for rent at a lower cost. In this study, a closed-loop supply chain with an AM hub (CLSCAM) is first designed. Thereafter, to support manufacturers in making the decision to adopt AM, two models are developed: sustainability (cost, environment, and time) evaluation model from the lifecycle perspective of CLSCAM, and a PC method is developed to maximize the three sustainability indices. Since the PC problem with complex product structure is an NP-hard problem, the genetic algorithm is employed as a solution method. Furthermore, an experimental analysis is conducted to validate the proposed model through a real-world application (testbed product). The results reveal that the AM hub and PC model can effectively improve the sustainability of the entire lifecycle. In particular, the results of improved sustainability per unit product in mass production scenarios demonstrate the practical applicability of the proposed model. These results also demonstrate that the pre-manufacturing stage has the greatest impact on the cost sustainability index in the CLSCAM. It is further confirmed that the sustainability improvement effect of PC increases with increasing AM raw material consumption efficiency, volume reduction rate of PC.

Nijenhuis operators, product structures and complex structures on Lie–Yamaguti algebras

In this paper, first, we study linear deformations of a Lie–Yamaguti algebra and introduce the notion of a Nijenhuis operator. Then we introduce the notion of a product structure on a Lie–Yamaguti algebra, which is a Nijenhuis operator [Formula: see text] satisfying [Formula: see text]. There is a product structure on a Lie–Yamaguti algebra if and only if the Lie–Yamaguti algebra is the direct sum of two subalgebras (as vector spaces). There are some special product structures, each of which corresponds to a special decomposition of the original Lie–Yamaguti algebra. In the same way, we introduce the notion of a complex structure on a Lie–Yamaguti algebra. Finally, we add a compatibility condition between a product structure and a complex structure to introduce the notion of a complex product structure on a Lie–Yamaguti algebra.

Ocena technologiczności konstrukcji montażu według zmodyfikowanej metody Boothroyda & Dewhursta DFA

Paper presents the problem of evaluating manufacturability of product design. The issue was described from the point of view of course of assembly operations implementation criterion (Design for Assembly – DFA). Technological assessment of the complex product structure flow is given using Boothroyd & Dewhurst method. Presented flow of the proceedings is illustrated by an example.

A model for assessment of the impact of configuration changes in complex products

An assessment of the impact of configuration changes in complex products is significant for improving the accuracy of change decision-making. Most related studies lack objectivity, systematicness and applicability. For this reason, a four-phase model for the assessment of this impact is proposed. In Phase I, a network model for parameter relationships of complex products is built to accurately express the complex product structures. In Phase II, an assessment method for the change propagation probability based on the gray comprehensive relation analysis and an assessment method for the propagation impact probability via the analysis of configuration change values are proposed to compute the two probabilities objectively. In Phase III, the change propagation method is introduced to precisely assess the impact of the configuration changes between two parameters. In Phase IV, a method for assessing the overall impact of configuration changes via the division of the parameters into stages is put forward to systematically assess the impact of configuration changes on the whole complex products. The methods in the four-phase model are easy to program and could further improve the assessment efficiency. Besides, a practical application of the proposed assessment model is suggested to verify the validity and applicability of this research.

Cheminformatic Analysis of Natural Product Fragments.

Fragment-like natural products play a pivotal role in natural product research given their improved synthetic and computational tractability as well as commercial availability compared to more complex natural product structures. A multitude of computational tools have been developed to support the generation, analysis, and application of natural fragments for drug discovery and chemical biology research. In this contribution, the challenges and opportunities in such workflows are discussed and contextualized. Multiple successful applications and validations discussed herein attest to the relevance of natural fragments for drug discovery and the utility of machine learning and data science to support such endeavors.