Product Family Research Articles

Intersecting families of transformations

Consider [Formula: see text] and [Formula: see text] to represent the full transformation semigroup and the symmetric group on the set [Formula: see text], respectively. A subset [Formula: see text] of [Formula: see text] is called an intersecting family if any two transformations [Formula: see text] coincide at some point [Formula: see text]. An intersecting family [Formula: see text] is called maximum if no other intersecting family [Formula: see text] exists with [Formula: see text]. Frankl and Deza [On the maximum number of permutations with given maximal or minimal distance, J. Combin. Theory Ser. A 22(3) (1977) 352–360] established that the cardinality of a maximum intersecting family of [Formula: see text] equals [Formula: see text]. Subsequent research demonstrated that a maximum intersecting family of [Formula: see text] forms a coset of a stabilizer of one point, as shown by Cameron and Ku [Intersecting families of permutations, European J. Combin. 24(7) (2003) 881–890] and independently by Larose and Malvenuto [Stable sets of maximal size in Kneser-type graphs, European J. Combin. 25(5) (2004) 657–673]. Define [Formula: see text], where [Formula: see text] denotes the image set of [Formula: see text]. This paper presents a formula for the cardinality of a maximum intersecting family of [Formula: see text]. It then characterizes the maximum intersecting families of [Formula: see text] and concludes by determining the number of maximum intersecting families of [Formula: see text].

Genome mining of labdane-related diterpenoids: Discovery of the two-enzyme pathway leading to (-)-sandaracopimaradiene in the fungus Arthrinium sacchari.

Labdane-related diterpenoids (LRDs) in fungi are a pharmaceutically important, but underexplored family of natural products. In the biosynthesis of fungal LRDs, bifunctional terpene cyclases (TCs) consisting of αβγ domains are generally used to synthesize the polycyclic skeletones of LRDs. Herein, we conducted genome mining of LRDs in our fungal genome database and identified a unique pair of TCs, AsPS and AsCPS, in the fungus Arthrinium sacchari. AsPS consists of catalytically active α and inactive β domains, whereas AsCPS contains βγ domains and a truncated α domain. Heterologous expression in Aspergillus oryzae and biochemical characterization of recombinant proteins demonstrated that AsCPS synthesized copalyl diphosphate and that AsPS then converted it to (-)-sandaracopimaradiene. Since AsPS and AsCPS have distinct domain organizations from those of known fungal TCs and are likely generated through fusion or loss of catalytic domains, our findings provide insight into the evolution of TCs in fungi.

Design of product configuration systems supporting customised product cost estimation using object-oriented ontology framework

The manufacturing sector is undergoing a significant transformation driven by the demand for personalised products, challenging manufacturers to provide precise quotations while maintaining cost control and profitability. Product Configuration Systems (PCS) play a pivotal role in supporting product configurations, facing challenges such as data integration, cost calculation relevance, and the need for a knowledge expression framework. This study significantly contributes by delineating an object-oriented ontology framework tailored for configurable product families within PCS. It incorporates comprehensive domain information models for MBOM, inventory, purchase, manufacturing, and sales and distribution. Additionally, the study proposes a domain information model-based cost estimation, integrating actual values from existing Enterprise Resource Planning (ERP) systems for various cost aspects. Design patterns for transforming domain information models into system implementations are introduced, covering both data and business operation layers. Practical application and feasibility are demonstrated through a detailed case study, emphasising the method's practicality. The proposed approach empowers manufacturers to derive accurate product cost estimates, supporting well-informed business decisions. Future research directions involve refining product model configurations, expanding support for diverse product types, and integrating additional digital technologies for an enhanced user experience. Further exploration of labour, equipment, and engineering design expenses aims to enhance cost estimation accuracy.

Local features: Enhancing variability modeling in software product lines

Context and motivation:Software Product Lines (SPL) enable the creation of software product families with shared core components using feature models to model variability. Choosing features from a feature model to generate a product may not be sufficient in certain situations because the application engineer may need to be able to decide on configuration time the system’s elements to which a certain feature will be applied. Therefore, there is a need to select which features have to be included in the product but also to which of its elements they have to be applied. Objective:We introduce local features that are selectively applied to specific parts of the system during product configuration. Results:We formalize local features using multimodels to establish relationships between local features and other elements of the system models. The paper includes examples illustrating the motivation for local features, a formal definition, and a domain-specific language for specification and implementation. Finally, we present a case study in a real scenario that shows how the concept of local features allowed us to define the variability of a complex system. The examples and the application case show that the proposal achieves higher customization levels at the application engineering phase.

Optimal Sustainable Manufacturing for Product Family Architecture in Intelligent Manufacturing: A Hierarchical Joint Optimization Approach

As consumers and governments prioritize cost-effectiveness and ecological sustainability, the limitations of traditional manufacturing paradigms become apparent in the context of constrained resources. The adverse effects of these paradigms on the environment and society hinder the achievement of a sustainable product life cycle. Intelligent manufacturing processes offer a solution by efficiently gathering meaningful data, such as usage and product recycling information, from previous product generations to enhance product design and subsequent sustainable manufacturing processes (SMPs). Modular product family architecture (PFA) design holds promise in promoting product sustainability and addressing diverse consumer needs. PFA design and SMPs are inherently interconnected within intelligent manufacturing frameworks. This paper aims to integrate the decision-making processes underlying PFA with SMPs. We model integrated PFA and SMP decisions as a Stackelberg game, which involves hierarchical joint optimization (HJO) for assessing product modularity and sustainable manufacturing fulfillment. We develop a bilevel 0–1 integer nonlinear programming model to represent the HJO decision-making process and propose a nested genetic algorithm (NGA) to solve the HJO problem. A case study with a laptop is conducted to validate the feasibility and potential of the proposed HJO model for joint optimization problems in PFA design and SMPs.

Task derivation and decomposition in crowdsourced manufacturing by bilevel coordinated optimization of product family planning and manufacturer load balancing

Crowdsourcing in manufacturing enables collaborative product fulfillment through supply contracting, aligned with task derivation and decomposition. Effective coordination of product family planning (PFP) with manufacturing processes is crucial for manufacturer load balancing (MLB). This paper focuses on game-theoretic decisions in crowdsourcing task derivation and decomposition, proposing a bilevel coordinated optimization model formulated as a Stackelberg game. PFP decisions are treated as profit maximization at the upper level, while MLB decisions are formulated as cost minimization at the lower level. A nested-bilevel genetic algorithm is developed for efficient model solution. A case study of tank trailer crowdsourced manufacturing demonstrates the benefits of employing the bilevel game-theoretic decision model, achieving optimal task derivation and decomposition and coordinated solutions for both the platform and crowdsourced manufacturers.

Non-modular fatty acid synthases yield distinct N-terminal acylation in ribosomal peptides.

Recent efforts in genome mining of ribosomally synthesized and post-translationally modified peptides (RiPPs) have expanded the diversity of post-translational modification chemistries. However, RiPPs are rarely reported as hybrid molecules incorporating biosynthetic machinery from other natural product families. Here we report lipoavitides, a class of RiPP/fatty-acid hybrid lipopeptides that display a unique, putatively membrane-targeting 4-hydroxy-2,4-dimethylpentanoyl (HMP)-modified N terminus. The HMP is formed via condensation of isobutyryl-coenzyme A (isobutyryl-CoA) and methylmalonyl-CoA catalysed by a 3-ketoacyl-(acyl carrier protein) synthase III enzyme, followed by successive tailoring reactions in the fatty acid biosynthetic pathway. The HMP and RiPP substructures are then connected by an acyltransferase exhibiting promiscuous activity towards the fatty acyl and RiPP substrates. Overall, the discovery of lipoavitides contributes a prototype of RiPP/fatty-acid hybrids and provides possible enzymatic tools for lipopeptide bioengineering.

Full biosynthetic pathway of pyrrolobenzoxazines

Pyrrolobenzoxazines are a rare terpene-amino acid family of natural products with potent biological activities. Here, we reported the full biosynthetic pathway of paeciloxazine (1), a typical pyrrolobenzoxazine, with significant insecticidal activity. Base on heterologous expression, chemical complement experiment, and in vitro biochemical assays, we demonstrated the sesquiterpene portion of 1 derived from discontinuously oxidations of amorphdiene, in which P450 monooxygenase PaxH catalyzed a cascade of hydroxylation and epoxidation, while two flavin dependent monooxygenases are involved in the transformation of the esterified tryptophan into a pyrrolobenzoxazine core. Furthermore, a total of 15 compounds were generated through heterologous expression, of which 13, 17 and 20 showed potential antiepileptic activity. This study fully elucidated the biosynthetic pathway of paeciloxazine (1) and showed the diversity and complexity of constructing natural products by organisms.

Decylprodigiosin: a new member of the prodigiosin family isolated from a seaweed-associated Streptomyces.

Bioprospecting actinobacterial secondary metabolism from untapped marine sources may lead to the discovery of biotechnologically-relevant compounds. While studying the diversity and bioactive potential of Actinomycetota associated with Codium tomentosum, a green seaweed collected in the northern Portuguese cost, strain CT-F61, identified as Streptomyces violaceoruber, was isolated. Its extracts displayed a strong anticancer activity on breast carcinoma T-47D and colorectal carcinoma HCT116 cells, being effective as well against a panel of human and fish pathogenic bacteria. Following a bioactivity-guided isolation pipeline, a new analogue of the red-pigmented family of the antibiotics prodigiosins, decylprodigiosin (1), was identified and chemically characterized. Despite this family of natural products being well-known for a long time, we report a new analogue and the first evidence for prodigiosins being produced by a seaweed-associated actinomycete.

Synthetic Studies toward Pseudolaric Acids: Radical Cyclization to Form Bridged Scaffold

Comprehensive SummaryPseudolaric acids are a family of diterpenoid natural products that exhibit a broad spectrum of biological activities. The main structural feature of their framework is a trans‐fused perhydroazulene bearing a bridged lactone positioned at the junction of the rings. Herein, we have developed a radical cyclization strategy that allows flexible tuning of the cyclization process through diverse silicon substitutions on the substrates. This strategy can assist in constructing a series of skeletons with structural resemblance to pseudolaric acids and expedites the construction of the bridged lactone. Finally, it facilitates the synthesis of the entire skeletal structure of the pseudolaric acid family of natural products, excluding the B‐ring functionalization.

Chen inequality for general warped product submanifold of Riemannian warped products I×fSm(c)

In the present paper, we investigate the geometry and topology of warped product submanifolds in Riemannian warped product I×fSm(c) and obtain the first Chen inequality that involves extrinsic invariants like the mean curvature and the length of the warping functions. This inequality also involves intrinsic invariants (δ-invariant and sectional curvature). In addition, an integral bound is provided for the Bochner operator formula of compact warped product submanifolds in terms of the gradient Ricci curvature. Our main object is to apply geometrically to number structures and obtained applications of Dirichlet eigenvalues problems. Some new results on mean curvature vanishing are presented, and a partial solution can be found to the well-known problem given by S S Chern. The family of Riemannian warped products generalized to Robertson-Walker space-times

A Sustainable Product Multi-Platform Planning Model for Assembly and Disassembly Process

Abstract The development of a product platform is an effective strategy to respond to dynamic market demands, decrease lead time, and delay product differentiation. However, the traditional product platform configuration method cannot satisfy the sustainability requirements for modern products. To solve this problem, a sustainable product multi-platform (SPMP) model for assembly/disassembly technology is proposed in this article. The proposed SPMP model measures the energy consumption of module instances during the installation based on the platform-based assembly index (PAI) and platform-based disassembly index (PDI), and provides a multi-platform solution for the assembly of the product family. To demonstrate the effectiveness of the proposed method, two product family cases are discussed. A simplified case shows that multi-objective particle swarm optimization (MOPSO) algorithm has a stronger optimization ability than the linear programing method in reducing the product processing cost. The hair dryer family case demonstrates that the proposed method reduces the energy consumption during assembly by linking sustainability to the product design.

Enabling the identification of multi-product assembly system architectures – a new method and its application in the automotive industry

Product variety, in combination with today’s unstable market environment, brings strong challenges to manufacturing firms. Single-product assembly systems become difficult to implement as the return on investment is difficult to obtain with decreasing lot sizes and unstable customer demands. Multi-product assembly systems are a possible solution to this problem, as they allow to compensate demand fluctuations throughout the product mix. However, variety is a strong barrier to this kind of production systems. A new method is presented in this paper to identify multi-product assembly system architectures adapted to a product family, based on the identification of components for common positioning. This method has been applied to a supplier in the automotive industry and a return of experience of this case study is provided, highlighting its potentials and barriers.

A systematic approach for simulation-based dimensioning of production systems during the concept phase of factory planning

Due to increasing globalization, market penetration, and technological progress, more products are becoming highly standardized and interchangeable. This has led to fierce price competition, forcing companies to compete for declining margins. To remain competitive in the long term, it is essential to consider both changeability and profitability during the early planning phases. The article proposes an approach for simulation studies using discrete-event simulation during the concept phase of factory planning. This approach aims to systematically dimension production resources while considering alternative scaling options, such as a higher degree of automation. By doing so, the approach facilitates the demand-oriented deployment of resources during the ramp-up phase, which helps to control and reduce manufacturing costs. The simulation experiments yield scaling paths that indicate the timing and quantity of resources required to meet changing demands. These paths form the basis for subsequent factory planning steps. For instance, the layout can incorporate the necessary space for a future automation solution that will be profitable, enabling faster adaptation to demand changes and securing competitive advantages. This is demonstrated in a use case where the approach was applied to the factory planning of a new production system for a sensor product family.

New product family demand planning: AddressingSKU‐level spread bias

AbstractNew product supply chain planning is challenging, primarily due to the lack of historical demand data. Rarely, however, do the academic literature or companies differentiate the demand forecasting process for new products from existing ones, despite their increased reliance on judgmental estimates. This research focuses on how judgmental errors lead to an under‐estimation of the difference between the highest‐ and lowest‐demand stock‐keeping units (SKUs), and consequently negatively impact supply chain planning for new product family introductions. A generalized empirical model and accompanying discrete event simulation are developed and applied to data from a major consumer packaged goods (CPG) firm during the launch of a new cosmetics product family. This application allows us to identify a focal type of judgmental error (identified as the SKU‐level spread bias) inherent to new product forecasting and to provide a new theoretical understanding of how this type of bias harms supply chain performance. Via an empirically driven theory‐building approach that iterates between the simulation outcomes and existing literature, SKU‐level spread bias is demonstrated to harm demand forecasts and, thereby, supply chain plans. Our unique theory‐building approach advances theory by identifying planner SKU‐level spread bias as a new source of bias that firms should seek to mitigate when introducing new product families.

Evaluation of the FluoroType Mycobacteria assay for identification of mycobacteria.

This study is the first clinical evaluation report of the novel FluoroType Mycobacteria assay. The assay has the potential to replace the established GenoType NTM product family in identification of culture-enriched mycobacteria. However, our research results suggest that the assay performs suboptimally and may not be feasible for use in all clinical settings.

The Growth Engine Concept and Its Potential for an Electrified Aviation Future

Abstract The emerging need for cost- and energy-efficient propulsion systems have shifted the research interest to radical concepts, with several challenges to overcome in order to enter into service. However, revitalizing old yet provably successful engine designs—a practice followed by engine manufacturers over the years—can provide low-risk alternative solutions to move immediate market demands. The paper reviews this approach, known as concept of growth engines or core commonality, and investigates how a geometrically fixed or geometrically similar engine core can be utilized across a family of engines. The development programs of the highly successful CFM56 and PT6 engine families are analyzed, proving the success of this concept over the years. The idea is based on the engineering paradigm of product families and is briefly presented from a theoretical perspective. Implementation methods and simulation tools to initiate, conceptualize, design, and evaluate an engine family program are reviewed. The potential application of engine core commonality into electrified propulsion systems is investigated. Design challenges and opportunities that electrification imposes to the growth engine concept are discussed. Finally, the concept of growth electrified propulsion systems is introduced, conveying future research directions to achieve a successful family of engines for electrified applications.

Green product family design with low-carbon postponement fulfilment: A bilevel interactive optimization approach

In the globalization process, postponement is still an effective strategy for enterprises to reduce supply chain risks and uncertainties. The enterprises must additionally consider low-carbon issues in product development process with the increasing environmental concerns. The inherent coupling of product design and postponement fulfillment that considers environmental concerns necessitates joint optimization of green product family (GPF) design and low-carbon postponement (LCP) fulfillment. However, existing literature tends to aggregate the postponement and environmental concerns into a single-level and all-in-one optimization problem based on the assumption that a (fixed) GPF architecture is pre-determined at the outset. Different from existing modes, this article proposes a bilevel interactive optimization (BIO) approach to reveal the hierarchical interactions and complex decisions involved in GPF design and LCP fulfillment. Based on bilevel programming theory, a non-linear BIO model consisting of an upper-level GPF design problem and two lower-level LCP fulfillment problems is established. A nested genetic algorithm is developed to solve the proposed BIO model. A case study of LCP manufacturing of a green electric vehicle product family is adopted to verify the feasibility and superiority of the BIO approach for the GPF design and the LCP fulfillment. Some important managerial insights are derived from the comparison experiments and the sensitivity analysis on the proposed demand postponement parameter.

Product family modeling technology for customized cosmetic packaging design based on basic-element theory

BackgroundAs the market demands change, SMEs (small and medium-sized enterprises) have long faced many design issues, including high costs, lengthy cycles, and insufficient innovation. These issues are especially noticeable in the domain of cosmetic packaging design. ObjectiveTo explore innovative product family modeling methods and configuration design processes to improve the efficiency of enterprise cosmetic packaging design and develop the design for mass customization. MethodsTo accomplish this objective, the basic-element theory has been introduced and applied to the design and development system of the product family. ResultsBy examining the mapping relationships between the demand domain, functional domain, technology domain, and structure domain, four interrelated models have been developed, including the demand model, functional model, technology model, and structure model. Together, these models form the mechanism and methodology of product family modeling, specifically for cosmetic packaging design. Through an analysis of a case study on men’s cosmetic packaging design, the feasibility of the proposed product family modeling technology has been demonstrated in terms of customized cosmetic packaging design, and the design efficiency has been enhanced. ConclusionThe product family modeling technology employs a formalized element as a module configuration design language, permeating throughout the entire development cycle of cosmetic packaging design, thus facilitating a structured and modularized configuration design process for the product family system. The application of the basic-element principle in product family modeling technology contributes to the enrichment of the research field surrounding cosmetic packaging product family configuration design, while also providing valuable methods and references for enterprises aiming to elevate the efficiency of cosmetic packaging design for the mass customization product model.

Discovery of Diverse Sesquiterpenoids from Crossiella cryophila through Genome Mining and NMR Tracking.

Terpenoids, the largest and most structurally diverse natural product family, are predominantly found in fungi and plants, with bacterial terpenoids forming a minor fraction. Here, we established an efficient platform that integrates genome mining and NMR-tracking for prioritizing strains and tracking bacterial terpenoids. By employing this platform, we selected Crossiella cryophila for a comprehensive investigation of its capacity for terpenoid production, resulting in the characterization of 15 sesquiterpenoids. These compounds comprise nine new sesquiterpenoids (1-9), along with six known analogs (10-15), which are categorized into five distinctive carbon skeletons: bicyclogermacrane, maaliane, cadinane, eudesmane, and nor-eudesmane. Their chemical structures were determined through a combination of spectroscopic analysis, single-crystal X-ray diffraction, and quantum chemical calculations. Notably, the absolute configurations of compounds 1, 2, 5-7, 9, and 13-15 were determined via single-crystal X-ray diffraction analyses. The selected compounds were evaluated for their anticancer, antimicrobial, and anti-inflammatory bioactivities; however, none of these compounds displayed any significant bioactivity. This study enriches the repertoire of bacterial terpenoids, offers a practical process for prioritizing strains for bacterial terpenoids discovery, and establishes a foundation for exploring terpenoid biosynthesis.