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This article presents the research on the efficiency of performance of automatic design of variant products system, including the process of product variant configuration, preparation of the 3D model in CAD system and the preparation of the assembly instructions for the manufacturing positions. The variants of the described product take the form of various combinations of individual assembly parts combined together and constitute an example of customized products, and the process of their manufacture (assembly) is the subject of the research carried out in the SmartFactory Laboratory at the Poznan University of Technology.

Established companies are unmatched in developing sustaining innovations, but when it comes to disruptive products, new entrants often outperform them. Despite the implementation of ‘agile methods’ to enable shorter development cycles and continuous customer feedback, the success score of most corporates still lacks market-changing innovations. Disruption is a continuous process that should start with niche products focusing on insufficiently addressed customer needs and — given a positive market feedback — continue with new variants to gain market share step-by-step. Hence, a needs-oriented definition of the initial product offer followed by a need-based planning of future product variants are essential for a disruptive product strategy. Yet, companies' failure rates of ∼40% for new products show that the need-based definition of minimum viable products and the planning of later product generations is insufficient. In this paper, the authors present a framework for a disruption-oriented product planning process. Based on a literature analysis focused on methodologies supporting the development process of potentially disruptive innovations, basic criteria are derived and deficits of existing approaches are identified. The framework will help companies as a guideline to understand the overall process of how to develop disruptive innovations. It further explains the essential activities and their interactions.

This research entitled “Souvenir Models as an Improvement of Aesthetic Quality and Product Variety in Gembreng Crafts Center, PasarKabanganLaweyan Surakarta” in general aimed to improve the quality and product variants in Gembreng Crafts Center, PasarKabanganLaweyan Surakarta, followed by aesthetic product variants that are able to represent the city of Surakarta as an increasing competitiveness in the global market.  The specific purpose of this research is to develop the competitiveness of gembreng handicraft products with other souvenirs such as batik, wood or metal so as to attract the attention and interest of domestic and foreign tourists and indirectly also increase the income of the craftsmen. This research applied explorative exploratory research method. Therefore, it tends to be experimental; looking for novelty possibilities in the techniques and design of souvenir aesthetic products. Data collection techniques undertaken by researchers were observations and in-depth interviews at the gembreng industry center in Pasar Kabangan Laweyan, Surakarta. The subject of this research was the gembreng craftsmen, with the aim of knowing the techniques they use and the techniques that can be explored for new products planned. In addition, this study also interviewed some artists and culture bearers in Surakarta to find a visual image that can represent the city of Surakarta as a cultural city. Objects observed in this study were the results of the products that have been produced and the manufacturing techniques of handicraft products. It is important to look for various possibilities for the development of the planned product designs. The existing data were validated by data reduction techniques and then they were analyzed. The results of this analysis were the basis for the development of souvenir product designs in the gembreng crafts center, Pasar Laweyan, Surakarta. The results of this development research were in the form of prototype gembreng-based souvenir products with a variety of possible variants, both the form and creativity. It is expected that the visual image of this product can represent the city of Surakarta as a cultural city.  Keywords : souvenir, gembreng crafts,,Surakarta Â

An advanced version of the XTJ family of space solar cells called XTJ Targeted Environment (XTE) is being developed at Spectrolab. The XTE cell consists of four specifically designed product variants: standard radiation fluence (SF) for GEO missions, low radiation fluence (LF) for LEO missions, high radiation fluence (HF) for orbit transfer or MEO missions, and LILT for low intensity, low temperature outer planetary environments. The XTE SF and XTE LF variants have demonstrated an average AM0 efficiencies of 32.2% and 32.6% in multiple engineering confidence cell builds. The XTE LILT cells have also achieved an average BOL efficiency of 36.6% under AM0 5.5 AU, $- 140 ^{circ}\mathrm{C}$, 4.5 mW/cm$^{2}$ Jupiter conditions in an engineering confidence cell build. Three (SF, LF, and LILT) of the four XTE cell variants completed engineering confidence tests and are underway to complete AIAA-S-111 qualification.

Operations flow based similarity is an important criterion for grouping variants. Similarity coefficient for product variants with networked sequence of operations has not been considered in the literature. Previously proposed similarity coefficients, which are based on operation/assembly sequence, focused on variants with serial operations sequences where the order of processing operations is fixed; while in practice, there are many part/product variants with flexible operations sequence options. A novel similarity coefficient for part/product variants is proposed based on the networked operations sequence similarity inspired by the analysis used in the field of biology (e.g. enzymes structures comparison). An extension of the proposed coefficient is also presented with an example for illustration. A more comprehensive similarity coefficient is developed by including operations similarity and production volume criteria. The popular operations similarity coefficient, called Jaccard's similarity, is applied and extended. A new coefficient using volume similarity criterion is also developed. Part/product variants are then clustered and grouped based on the combined similarity coefficient using the average linkage clustering (ALC) algorithm. The main applications of the proposed similarity coefficient are addressed. The grouped variants are sequenced as a secondary application of the proposed similarity coefficient. The sequence obtained from the proposed approach is compared with that obtained from a developed mathematical model. The result shows the accuracy of the proposed sequencing approach and can serve as a good preliminary sequence. A case study is also provided for demonstration.

Accurate and precise quantitative measurement of product-related variants of a therapeutic antibody is essential for product development and testing. Bispecific antibodies (bsAbs) are Abs composed of two different half antibody arms, each of which recognizes a distinct target, and recently they have attracted substantial therapeutic interest. Because of the increased complexity of its structure and its production process, as compared to a conventional monoclonal antibody, additional product-related variants, including covalent and noncovalent homodimers of half antibodies (hAbs), may be present in the bsAb product. Sufficient separation and reliable quantitation of these bsAb homodimers using liquid chromatography (LC) or capillary electrophoresis-based methods is challenging because these homodimer species and the bsAb often have similar physicochemical properties. Formation of noncovalent homodimers and heterodimers can also occur. In addition, since homodimers share common sequences with their corresponding halves and bsAb, it is not suitable to use peptides as surrogates for their quantitation. To tackle these analytical challenges, we developed a mass spectrometry-based quantitation method. Chip-based nanoflow LC-time-of-flight mass spectrometry coupled with a standard addition approach provided unbiased absolute quantitation of these drug-product-related variants. Two methods for the addition of known levels of standard (multi- or single-addition) were evaluated. Both methods demonstrated accurate and reproducible quantitation of homodimers at the 0.2% (w/w) level, with the single-addition method having the promise of higher analytical throughput.

We focus on the problem of managing a collection of related software product variants realized via cloning. By analyzing three industrial case studies of organizations with cloned product lines, we conclude that an efficient management of clones relies on both refactoring cloned variants into a single-copy product line representation and improving development experience when maintaining existing clones. We propose a framework that consists of seven conceptual operators for cloned product line management and show that these operators are adequate to realize development activities we observed in the analyzed case studies. We discuss options for implementing the operators and benefits of the operator-based view.

Experiential teaching and research facilities such as learning factories provide a favorable environment and tools to develop, test and implement new products and manufacturing systems concepts and solutions. Learning factories that are geared towards the capabilities and requirements of changeable manufacturing systems (CMS) are used for validating new products, their variants and changeable production systems design, planning and control methods. Existing approaches of developing new products are reviewed, and a new approach to develop products for changeable learning factories is presented and validated by a case study. The new development approach is dedicated to changeable learning manufacturing systems by choosing a product line among many candidates to suite the learning system capabilities and desired learning outcomes. Designs for product variants that suite the learning factory and planned learning scenarios and training experience. This paper focuses on learning factories for changeable manufacturing systems, which are constructed to possess the necessary changeability enablers such as mobility, modularity, scalability, universality and compatibility. It is challenging to associate learning and research to a changeable manufacturing system.

Multi-variant products to be assembled on mixed-model assembly lines at locations within a production network need to be scheduled locally. Scheduling is a highly complex task especially if it simultaneously covers the assignment of orders, which are product variants to be assembled within a production period, to assembly lines as well as their sequencing on the lines. However, this is required if workers can flexibly fulfill tasks across stations of several lines and, thus, capacity of workers is shared among the lines. As this is the case for final assembly of the Airbus A320 Family, this paper introduces an optimization model for local order scheduling for mixed-model assembly lines covering both assignment to lines as well as sequencing. The model integrates the planning approaches mixed-model sequencing and level scheduling in order to minimize work overload in final assembly and to level material demand with regard to suppliers. The presented model is validated in the industrial application of the final assembly of the Airbus A320 Family. The results demonstrate significant improvement in terms of less work overload and a more even material demand compared to current planning.

While joining tolerances, and therefore forces, are known in the assembly process, the determination of disassembly forces is not possible. This is caused by changes of the product properties during the product operation, which has multiple reasons like thermal or mechanical stress on the product. Regarding the planning of disassembly tasks, disassembly times and tools cannot be planned properly. They have to be determined in the process or stay undefined, which can result in damaging of the product. This article shows an approach to describe the necessary disassembly forces without having to investigate the complex physical influences caused by the usage of the product. A solidifying force that has to be overcome in the disassembly process is defined. To make the solidifying force transferable within the huge amounts of individual products, it is split into a usage factor (e.g. hours of operation) and a product specific factor (e.g. geometry of connection), which specify the influences on the joint properties. The transferability of usage factor to product variants is investigated using a FEM-Simulation.

A key objective of self-adaptive systems is to continue to provide optimal quality of service when the environment changes. A dynamic software product line (DSPL) can benefit from knowing how its various product variants would have performed (in terms of quality of service) with respect to the recent history of inputs. We propose a family-based analysis that simulates all the product variants of a DSPL simultaneously, at runtime, on recent environmental inputs to obtain an estimate of the quality of service that each one of the product variants would have had, provided it had been executing. We assessed the efficiency of our DSPL analysis compared to the efficiency of analyzing each product individually on three case studies. We obtained mixed results due to the explosion of quality-of-service values for the product variants of a DSPL. After introducing a simple data abstraction on the values of quality-of- service variables, our DSPL analysis is between 1.4 and 7.7 times faster than analyzing the products one at a time.

Many ERP systems support configurable materials. Due to an ever increasing number of product variants the benefits of this approach are well understood. However, these implementations are not standardized. In this article we propose a new standard interface for the exchange of configuration data. This would lead to further benefits as systems as Advanced Planning systems could better use manufacturing flexibility while web shops as Amazon could easily integrate manufacturers of complex products with much reduced implementation effort.

The control of today's production systems is becoming more complex due to an increasing number of product variants, short-time delivery requirements and non-standardized production processes. Especially shop floors organized as job-shops are indispensable for single- and small-series-production with low repetition rates. Current tools for production planning like Advanced Planning and Scheduling (APS) systems support the creation of ideal production plans for this high complex production. However, appropriate methods for production control are not available, mostly due to a lack of transparency concerning the current production status. Hence, decisions to counteract disturbances and deviations from the plan are made locally by foremen or workers based on their experience and know-how. Due to their local field of view, it is often not possible to estimate the impacts on other orders in the production. The consequences are rush orders and high stock levels resulting in long and variable throughput times and at least in a decoupling of real and planned production. This paper presents a new approach for a job-shop control system based on a permanent adaption of the production plan to the current situation. A genetic algorithm for rescheduling the production plan centrally is the focused element of the described control system in this paper.

A new Co-platforming methodology is introduced for mapping product features platform and corresponding manufacturing system machines platform. A cluster of platform and non-platform system machines are derived using matrix formulation and manipulation. The objective of Co-platforming is to establish the mapping between platforms of products and manufacturing machines for use in synthesizing systems capable of adaptation to changes in product variants without significant changes in the platform machines. This prolongs manufacturing systems useful life and reduces the cost of re-tooling as products evolve and new models are introduced. Fabrication of automobile cylinder blocks is used for demonstration and verification.

Due to rising demand for customer-specific products, a growing number of product variants is increasing complexity in production systems. Since automated production systems are often not economical in high-variant production scenarios, human flexibility plays an important role. In recent years a variety of assistance systems have emerged that support manual work by collecting, processing and providing information. However, this technological leap is not widely applied in the industry yet. This paper presents an approach to application-specific design of assistance systems for manual work in production. Required assistance functions, application-specific requirements and a technology database are used for the preselection of technologies and components for an assistance system. Alternative assistance system solutions are generated according to application-specific needs and compared through an economic evaluation. An application of this approach is shown for a manual assembly system in the learning factory for cyber-physical production systems.

The article describes research on recycling-oriented analysis during product ecodesign. The study was conducted using a proprietary agent system operating based on the recycling-oriented product model. The analysis focused on a household appliance: an electric kettle. The authors developed a project of a new appliance and then created its geometric model in a CAD 3D system. Next, analyses were conducted to compare the recyclability of the appliance with different material and joint combinations. A total of 16 different variants of the appliance were designed within the project. Each of them was evaluated for its recycling parameters and cost of recycling.

The change propagation and prediction in a product family design is discussed in this chapter. In the present situation, product family design is a popular approach in the industry to meet the diversified design needs and customer preferences. In a product family, common components are used by different product variants. The changes in one product variant will flow to the entire family. Therefore, the prediction of change propagation in a family of the product is a challenging task. In the literature, various design change management methodologies have been proposed, but all these methods are limited to a single artifact.

Engineer-to-order-companies in the field of mechanical engineering are particularly facing the challenge of providing customized products at competitive prices while the market is increasingly fragmented into small niches. Striving to fulfill this demand, companies underestimate the negative financial effect of a higher product variety. Therefore, complexity costs for new product variants with small volumes are often only roughly estimated. This leaves a severe risk for crosssubsidization of exotic variants and a loss in the company's competitive market position. Previous research does not provide a holistic approach that considers the integration of complexity costs related to a new variant and the existing variants in the offer process. This paper introduces a methodology facing these challenges. Adjustments of product configurations during the configuration process are analyzed and taken into account in order to increase the transparency during this work-flow. Complexity costs of new customer specific product variants can be determined at an early stage of the offer process. By using similarity analysis, they are clustered and distributed to the causative department. Customers can thus be managed through the offer process and the pricing of the product can be optimized as the complexity costs are considered as well.

Transfer lines are employed for the mass production of fixed products or a very narrow range of product variants. This paper considers a simple transfer line balancing problem (TLBP) with a focus o...

In a supply chain environment, time delay has a significant impact on the success of perishable products. A major concern is therefore aimed at development of a holistic optimized approach in a supply chain environment for perishable products. Thus, integration of production, inventory and, distribution of perishable products in a supply chain environment are the challenging tasks for practitioners and researchers. In general, the standard optimal supply chain model cannot work for perishable products. There is therefore, a need for a holistic model that focuses on the consolidation of the processes. Shorter product shelf-life, temperature control, requirement of strict tractability, large number of product variants, and a large volume of goods handled are the major challenges in a supply chain environment for perishable products. The present work focuses on the development of a holistic model which uses improved bacteria forging algorithm (IBFA) for solving the formulated model. We have proposed and analyzed some general properties of the model and, finally applied it to a three-stage supply chain problem using an IBFA. Two case studies have been considered for support and demonstration of the integrated perishable supply chain network problem. Results obtained from IBFA reveal that the proposed model is more useful for decision makers while considering optimal supply chain network for perishable products. Finally, validation of results has been carried out using bacteria forging algorithm (BFA). The computational performance of the proposed algorithm proves that IBFA is instrumental in effectively handling the proposed approach.

Monoclonal antibodies (mAbs) are biological macromolecules with complex post-translational modifications that can be observed when assessing product variants. The N- and C-terminal heterogeneities of commercially produced antibodies have been observed and extensively studied over the past 30 years. This review summarizes the current literature on detectable antibody termini variants from cultured cells. The presence of these heterogeneities can be detected by many different analytical methods, mostly based on sequence, charge and size differences. Examples are presented that highlight terminal heterogeneities, methods of detection, and their impact on the quality of mAbs. Regulatory considerations are also discussed regarding the potential impact on product quality, safety, and efficacy.

Smart CAD/CAM technologies for superior product modeling in the intelligence of designing complete product variants become more and more pertinent in future. Many design techniques to help interdisciplinary design actions in different engineering domains in addition to consequent processes have to be developed. A necessary job to achieve this aim is to permanently investigate the present state of the art, emerging trends, new approaches, in addition to industrial problems and requirements about the entire CAD/CAM area. With the aim of direct future research and development activities as close as possible to the continuously rising requirements of a worldwide market we carried out a wide-ranging national study in cooperation with one of the Germans leading CAD/CAM magazines. In this way, it became possible to reach a representative amount of users, to obtain their experience based assessments on today’s most important aspects of CAD/CAM technology. The results of this examination are summarized in this paper to give system developers, engineers, and researchers an overview of the present condition as well as to serve as a direction for decision makers in the Design and Development areas.

Manufacturing activities are characterised by high repetitiveness and the generation of vast amounts of data, which however remain underutilised and in most cases completely unexploited. However, new design and planning projects share numerous commonalities in their processes, materials and resources with past cases. Leveraging information, which is created and distributed among workers, departments and partners of a company through its transformation into knowledge can enable the coordination between the phases of product design and manufacturing, especially in the context of engineered-to-order products. Knowledge intensive industrial sectors that manufacture one-of-a-kind products or several product variants, such as the mould-making, can benefit from the reutilisation of past knowledge. This research work aims to the systematic capturing, storage and retrieval of knowledge about engineering projects and enable its reuse in the design and planning phases. The case-based data model, the components of the knowledge reuse engine and a set of knowledge enriched apps are presented. The application of the framework is demonstrated through a real-life case study with data coming from the mould making industry.

Analyzing the sales process of many companies in the field of mechanical engineering leads to the conclusion that companies try to satisfy customer requirements at any price instead of offering standard or slightly modified variants to the customer. That would cause much less internal effort. As a result, exotic product variants are often sold unprofitably, since dissimilar products are, of course, more expensive than standard variants due to higher adjustment costs for their development. Until now there is no systematic approach that identifies and visualizes preferable variants for different segments which can be offered to the customer in order to set an anchor for the following configuration and detailing of the product variant. In this paper, a methodology is presented that allows companies to describe and visualize product variants from different perspectives in an integrated way based on similarities between product variants. The paper focuses on the identification and visualization of similarities between product variants and the determination of preferable product variants in different product segments. Similarities are identified with the help of features and specifications covering two major levels: the market level and the customer requirements level. Similarities between product variants are shown on each level by multidimensional scaling, which allows a simple visual evaluation.

In this study, we investigate newspapers' decision to expand their product lines by adding online editions that incorporate user-generated content. We demonstrate that such product line extensions mitigate the extent of slanting in print media. The results also show that as the extent of discretion of users to generate online content increases, print versions of newspapers become more polarized. Furthermore, adding online editions results in reduced profits for newspapers as the additional product variants increase the intensity of competition in the market and the discretion awarded to users limits the ability of newspapers to extract rents from consumers. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2013.1746 . This paper was accepted by J. Miguel Villas-Boas, marketing.

Mass customisation involves the provision of product variants that fulfil clients' specific requirements seeking to increase product values. The configuration process involves a chain of decisions, which needs to be undertaken to create product variants that meet each client specific requirements. In this paper, this chain of decisions is conceptualized in terms of customisation units. Each customisation unit encompasses a customisable attribute (e.g. size, colour) and the range of items offered for this attribute. A design science approach was adopted in this investigation. In this approach, knowledge is produced by creating and testing a solution, which provides practical and theoretical contributions. A method is proposed to analyse and improve the configuration process by conceptualizing this process as a tree diagram. The proposed method is used to analyse the configuration process developed by organisations of the house-building sector based in the U.K. and Brazil: a manufacturer of floor tiles, contractors, and registered providers. These analyses enabled a comparison of the distinct configuration processes adopted. In addition, problems associated to the configuration process (such as burden of choice) and opportunities for improvements were also identified. Finally, alternative chains of decision were also devised based on these analyses to address the problems identified.

Design of complex configurable products is a hard task. Testing of all variants is often impossible because the number of variants is orders of magnitude larger than the total life cycle production volume. Modular design is advocated as solution but cannot guarantee that if one variant works OK another will not cause errors. This paper proposes, based on a similar method for modular database system design, a theory for modular design of mechanical systems that poses the concept of module independence, to enable design and test of module families as a separate unit while offering formal conditions to assure that no variant of the module family will cause failures when integrated in the end-product. This allows system verification and testing to be done per module family with no need to test individual end product variants. The method is illustrated with a simple example of a mechanical design, but not yet applied in practice.

We study a firm's manufacturing strategy under two types of flexible production technologies: the traditional flexible technology and 3D printing. Under the traditional flexible technology, capacity becomes more expensive as it handles more product variants; under 3D printing, however, capacity cost is independent of the number of product variants processed. The firm adopts a dedicated technology and one type of flexible technology, either the traditional one or 3D printing. It needs to choose an assortment from a potential set of variants, assigns each chosen variant to a production technology, and finally invests in capacities. We first establish that the optimal assortment must contain a number of the most popular variants from the potential set. Based on the variants' popularity rankings, we find that the optimal technology assignment can follow an unexpected reversed structure under the traditional flexible technology, while the optimal assignment always follows an ordered structure under 3D printing. Surprisingly, we find that adopting the traditional flexible technology in addition to the dedicated one may reduce product variety chosen by the firm. 3D printing, by contrast, always enhances product variety. Furthermore, 3D printing allows the firm to choose a much larger assortment than optimal without significant profit loss. These results demonstrate that the rising 3D printing has significantly different implications for firms' assortment and production strategy than the traditional flexible technology.

The increasing individualization of products is an enormous challenge for manufacturing companies. An increase of product variants and thus product complexity leads to increased process complexity within productions. An option to face this challenge is the segmentation of productions. Unfortunately, it is hardly possible to assess segmentation and the corresponding control strategies by using common methods, such as value stream mapping. Therefore, a simulation-based approach to assess segmentation and control strategies within multi-variant productions is shown in this paper. The approach is applied for a multi-variant production for medical equipment. Besides the development of the approach, the paper also shows the assessment results for the case study production.

This paper defines open-architecture products (OAPs), a new class of products comprising a fixed platform and modules that can be added and swapped. Customers can adapt OAPs to their needs by integrating modules into the platform. Manufacturers will produce these platforms, while new small companies and customers will develop the modules, thus increasing employment and causing the economy to flourish. At the same time OAPs will provide consumers with the product they desire. Challenges include developing new OAP design software for non-professional designers and new assembly systems to facilitate economical assembly of a large number of product variants.

The requirements of manufacturing companies are growing continuously. The customers demand more and more product variants, shorter delivery times and declining prices. To meet these demands, the production needs to be more flexible, highly automated and changeable. Future success is determined by companies’ capability to adapt their factory to this dynamic environment. The future is less predictable than it used to be. One way to consider this, is to look at different future scenarios. This paper shows a scenario- based simulation approach that uses scenario technique, morphological analysis and discrete event simulation to find out factory layout variants that are adequate for future requirements. The approach is verified by a case study.

This paper is about issues experienced along testing large-scale industrial products, with safety and security critical relevance. The challenges in testing - several thousand requirements for several product variants and various configurations - were addressed by test execution automation. However, since principal testing concepts as well as architectural concepts were ignored or poorly implemented, the test automation activities faced various difficulties within the considered projects. The current paper presents these issues in an abstracted manner and discusses possible solutions.

By applying biological pedigree concept into product conceptual structure design, an conceptual structural design approach is set forth to make full use of creative and innovative intelligence of living systems for design automation. According to the relationship between different product structures with same function, the classification model of product pedigree is established, which can be used as unified functional isomorphic model during the intelligent conceptual design process. On the other hand, according to the evolutional logic from quality change to quantities change, pedigree based product evolutionary design strategy is given. Product pedigrees which are homology dependent are used as basic evolutionary models, based on which, the parameter based, interaction field based and interaction mater based evolutional conceptual design method are proposed, respectively. Based on the relation network of the pedigree units, multiple variant design schemes can be obtained, which is a strong backbone to the innovative design process. Finally, design examples are used to demonstrate the successful application of the proposed pedigree based evolutionary method in the product variant design.

Constraint-based variability modeling is a flexible, declarative approach to managing solution-space variability. Product variants are defined in a top-down manner by successively restricting the admissible combinations of product artifacts until a specific product variant is determined. In this paper, we illustrate the range of constraint-based variability modeling by discussing two of its extreme flavors: constraint-guarded variability modeling and constraint-driven variability modeling. The former applies model checking to establish the global consistency of product variants which are built by manual specification of variations points, whereas the latter uses synthesis technology to fully automatically generate product variants that satisfy all given constraints. Each flavor is illustrated by means of a concrete case study.

Product customization is attracting more attentions in industry as a viable strategy to better meet customer requirements and gain more profit. However the vast number of product variants in product customization process often makes it difficult for consumers to make purchase decisions, a phenomenon referred to as information overload. In this paper we take a two-prong approach to tackle the issue of information overload in customized products recommendation. Basically, the method answers two questions, namely, which products to recommend and in what order to present the recommendations. Firstly, a probability relevance model is deployed to calculate the probability of relevance for each end product. Then a probability ranking principle is exploited to present the recommendations. The approach also takes customer flexibility into consideration and thus mitigates the effect of inconsistent specifications from customers. It does not require any prior knowledge about an active customer's preference and can accommodate the new customers challenge facing by recommendation approaches. Analytical results show that the method is optimal in terms of customer's utility and product recommendation efficiency. Numerical experiments are also conducted to test the presented approach.

Characteristic part family definition, part family master model feature diagram and XML stored document of master model are given for product variant design. Then, variant design process of part family is elaborated, including searching similar parts and the similarity retrieval mechanism which are studied for the product variant design of part family. Finally, the standard part family and business part family are developed through Java, Pro/E, SQL Server and an example on product variant design is given to testify the validity of characteristic part family and similarity retrieval mechanism.

For the purpose of solving product variant search and retrieval problems for non-professional customers, a search and retrieval framework is proposed based on the semantically annotated product family using multi-facet domain ontology. The method of developing multi-faceted domain ontology is discussed, and the annotation model is constructed，then the methodology of search and retrieval is presented in detail. Finally, an example of a digital camera family is employed to illustrate the proposed approach.

We investigate a firm's product line design and capacity investment problem for vertically differentiated products along design quality levels. Customers arrive according to a Poisson process and are heterogeneous in their marginal valuation of the quality level. Customers make product choices to maximize a linear utility function of price, quality level, and waiting cost. Resulting product demands are met through capacity investments in production processes, which are modeled as queuing systems. We consider two different types of production processes: product-focused, dedicated to the production of a single-product variant; and product-flexible, processing all product variants in the product line. Capacity investment and variable production costs are functions of the processed product's quality. We develop an integrated marketing-operations model that provides insights on the factors determining the right level of product variety to offer, the relative quality positioning of the products in the line, the resulting market coverage and segmentation, and the effects on production costs and congestion levels of the processes. We show that the statistical economies of scale resulting from the congestion phenomena in the production system impose limits on the optimal product variety. For product-focused processes the market size promotes a higher optimal product variety, whereas the per-unit capacity investment and customer waiting costs act as deterrents for higher product variety. For product-flexible processes optimal product variety also depends on the specific type of flexibility and the ratio of capacity investment to variable production costs.

This research was conducted at a company that produces paints such as wall paint, tile paint, floor paint, steel construction paint and many other types of paint. In addition to these types of paint, color and size are additional factors that cause high product variants. Inventory management with ABC analysis is very necessary to control a number of inventories by taking into account the value of the investment. Based on company conditions and literature, the purpose of this study is to be able to classify inventory in the company and be able to determine inventory control based on ABC classification. The research method is divided into four stages, namely data formulation, data collection, data processing, and analysis and conclusions. Data processed is in 2016, available product variants are 941 items with a total product value of Rp 15,477,094,182.00. The results of ABC analysis are 124 product items or 13.18% A class, 211 product items or 22.42% B class, and 606 product items or 64.40% C class of the total number of products available.Key words : Paint, Inventory Control, ABC Classification

Product variant design is one of the key technologies of Manufacturing Enterprise for responding market demand. During the product variant design, tolerance variant design plays an important role. However, tolerance variant design is considered rarely in the researches of product variant design. To solve the problem of tolerance design in product variant design, a component variant design method integrating dimension and tolerance is presented in this paper. The fundamental and implement of component dimension variant design is introduced. Through analyze the conventional tolerance design method; the status for tolerance variant with its implemental dimension is marked as fixed tolerance value, fixed tolerance grade and tolerance value variant with special regular. The equation of dimensional tolerance variants with the value of implemental dimension is presented. So the procedure of component variant design method integrating dimension and tolerance is proposed. Finally, a case study of output shaft of reducer illustrates the implemental process of proposed method. Result comparing with conventional method shows effectiveness of proposed method.

Companies are frequently using in-house developed scripts, macros and applications to support and automate the development of products and product variants. These items are often of different types creating a design platform with a multitude of dependencies. Such environments are often difficult to overview and maintain. In the current paper, an aerospace company with a design platform that has proven challenging to maintain has been studied. A method and limited software implementation have been tested and evaluated by interviewing four professionals at the company. The implementation provides a high granularity, which has been found to be necessary to give a quick platform overview and to facilitate maintenance and expansion of the design platform.

Platform and module planning results using traditional methods are usually not consistent with the actual situation in product family design (PFD). Research was conducted involving modularisation theory and implementation methods to overcome the difficulty of platform and module dynamic planning/re-design for mass customisation (MC). A graph-theoretical approach was also developed in PFD. Firstly, the commonality and the physical structure of the existing product variants were analyzed in a product family. Part commonality and the physical structure of similar products were then modelled using a directed and an undirected graph, respectively. According to market demands, different platform thresholds and boundary parameters of modules were set dynamically. The product platform and modules were then generated in a product family and the potential parts to be used were identified. Finally, the effectiveness of the proposed approach was demonstrated by the dynamic planning of the working devices of small wheel loaders.

Variant design of parts for mass customization is a rapidly custom process with standardized and modularized modules. Tabular layouts of article characteristics (TLAC) describe standardization and regularization information of product, and can expediently implement product variant design and variant response of process. On the basis of analyzing TLAC, combined with programming language Visual C++, an approach of part’s rapid responding design based on UG NX6.0 and TLAC was presented. The basic principle and the modeling method of master model technology based on TLAC were discussed. Finally, an application example of gear was given to verify the feasibility of the method

Delayed Product Differentiation (DPD) can reduce the manufacturing complexities arising due to the proliferation of products variety. A new optimization model constructs the optimum layout of delayed differentiation assembly lines for a mix of products to be manufactured by the same system and optimizes the position of the differentiation points. This model employs a classification tool (Cladistics) used in biological analysis and modifies it for use in planning DPD assembly lines configurations in order to incorporate the assembly precedence constraints, required production rates of different product variants and existing production capacity of work stations. The optimum layout configuration ensures that the quantities required of different products are produced on the same line; while achieving balance, minimizing duplication of stations and maximizing the overall system utilization. The developed model has been applied to a group of automobile engine accessories normally assembled on different lines. The use of Cladistics to analyze product variants that are candidates for delayed assembly is an original approach for designing the assembly line layout and identifying the best differentiation points. It also helps rationalize the design of product variants and their features to further delay their assembly differentiation and achieve economy of scale without affecting their functionality.

Product variant design is one of the key technologies of Manufacturing Enterprise for responding market demand. During the product variant design, dimensional tolerance variant design plays an important role. However, dimensional tolerance variant design is considered rarely in the researches of product variant design. To solve the dimensional tolerance variant design during product variant design, information expression, extraction and labeling method of dimensioning of dimensional tolerance of part dimension model is investigated. A variant design method with dimensional tolerance is presented in this paper. In the method, dimension variant design and dimensional tolerance variant design are integrated, so dimension variant design and dimensional tolerance variant design are implemented concurrently. A part variant design module with dimension and dimensional tolerance based on SolidWorks is developed for using Visual C++. Finally, an example of shaft illustrates the proposed method.

An increasing product variety causes different cost effects in several divisions of a company. These effects have to be identified in order to compare them to potential revenues. However, at the time strategic market decisions have to be made, not all detailed information about product variants and quantities are available. Analyses of future cost development and the choice of the manufacturing system are difficult and uncertain. Within the framework of the project “VireS” a simulation algorithm was developed at the Institute of Production Science (wbk) to simulate future developments of life cycle costs of manufacturing systems depending on quantities and varieties in an uncertain environment.

Motivated by the recent success of integer programming based procedures for computing discrete forecast horizons, we consider two-product variants of the classical dynamic lot-size model. In the first variant, we impose a warehouse capacity constraint on the total ending inventory of the two products in any period. In the second variant, the two products have both individual and joint setup costs for production. To our knowledge, there are no known procedures for computing forecast horizons for these variants. Under the assumption that future demands are discrete, we characterize forecast horizons for these two variants as feasibility/optimality questions in 0–1 mixed integer programs. A detailed computational study establishes the effectiveness of our approach and enables us to gain valuable insights into the behavior of minimal forecast horizons.

This paper applied conjoint analysis to elicit consumer preferences over attributes of functional foods and nutraceuticals using probiotics as the functional compound of interest. Data were gathered through a mall intercept survey in Guelph, Canada. Cluster analysis and chi-square tests were used to examine the relationship between respondents' characteristics and preferences for product variants. On the basis of cluster analysis of the part-worth scores from the conjoint analysis, three clusters were identified. Clusters differed predominantly according to the preferred mode of delivery and source of health claims. The value attached to health claims related to probiotics was also explored. The results suggested that consumers place a strong premium on claims verified by government, but little value on 'non-verified' claims made by product manufacturers.