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To ensure product quality within a manufacturing process, inspection processes are indispensable. One task of inspection planning is the selection of inspection characteristics. For optimization of costs and benefits, key characteristics can be defined by which the product quality can be checked with sufficient accuracy. The manual selection of key characteristics requires substantial planning effort and becomes uneconomic if many product variants prevail. This paper, therefore, aims to show a method for the efficient determination of key characteristics.

The authors present a novel Algorithm for the Selection of Key Characteristics (ASKC) based on an auto-encoder and a risk analysis. Given historical measurement data and tolerances, the algorithm clusters characteristics with redundant information and selects key characteristics based on a risk assessment. The authors compare ASKC with the algorithm Principal Feature Analysis (PFA) using artificial and historical measurement data.

The authors find that ASKC delivers superior results than PFA. Findings show that the algorithms enable the cost-efficient selection of key characteristics while maintaining the informative value of the inspection concerning the quality.

This paper fills an identified gap for simplified inspection planning with the method for the efficient selection of key features via ASKC.

Technology and market pressures are encouraging localized and small-series production in customer-driven industries. The purpose of this paper is to explore and understand the supply chain-, product- and process-design factors for small-series production in EU’s textile and apparel industry, to understand configuration decisions, priorities and challenges.

An interview study was undertaken with ten companies that represent diverse small-series production models and value chain roles. Interview data was analysed to identify supply network configuration characteristics, decision priorities and challenges.

Three small-series production models emerged from the analysis, differing with respect to adoption of process postponement and customization. The findings confirm and extend past research regarding diverse decision priorities and product, process, supply chain structure/relationship configurations. Challenges identified relate to planning (priorities) and implementation (configuration). Whereas competence availability and digital technology challenges are common, several difficulties are linked to production model like tensions related to priorities and small volumes, which are not found with customization.

Future research can make comparisons with other industry and location contexts; adopt dynamic approaches to distinguish between design and reconfiguration processes; and address indicated paradoxical-tensions.

The study findings can provide guidance for companies regarding identification of priorities and management of (planning/implementation) challenges impacting small-series production in T&A.

The paper brings a configuration perspective at the supply chain level to the problem of small-series production implementation, which demands holistic and context-specific understanding.

Manufacturing companies must have a good knowledge of their products and processes to be competitive. This is increasingly important as products become more complex. There are many recent developments in product representation, but these do not currently address manufacturing process issues, or integrate with techniques such as key characteristics and Variation Risk Management. This paper describes the development of a database which models complex product specifications, down to component feature detail. It allows the representation of manufacturing operations, process chains and costs, and maps these models. Key product characteristics are flowed down to the detailed feature level, and the associated variability and capability assessed. The paper commences by outlining some of the recent significant developments in product representation. The database structure and associated applications are described. Finally, an example is provided for the use of the database, based on the representation of gas turbine engine from a major aerospace manufacturing company.

This paper aims to present a case study of virtual-reality-based product demonstrations featuring items of furniture. The results will be of use in further design and development of virtual-reality-based product demonstration systems and could also support effective student learning.

A new method was introduced to guide the experiment by confirming orthogonal arrays. User interactions were then planned, and a furniture demonstration system was implemented. The experiment comprised two stages. In the evaluation stage, participants were invited to experience the virtual-reality (VR)-based furniture demonstration system and complete a user experience (UX) survey. Taguchi-style robust design methods were used to design orthogonal table experiments and planning and design operation methods were used to implement an experimental display system in order to obtain optimized combinations of control factors and levels. The second stage involved a confirmatory test for the optimized combinations. A pilot questionnaire was first applied to survey demonstration scenarios that are important to customers.

The author found in terms of furniture products, product interactive display through VR can achieve good user satisfaction through quality design planning. VR can better grasp the characteristics of products than paper catalogs and website catalogs. And VR can better grasp the characteristics of products than online videos. For “interactive inspection”, “function simulation”, “style customization” and “set-out customization” were the most valuable demonstration scenarios for customers. The results of the experiment confirmed that the “overall rating”, “hedonic appeal” and “practical quality” were the three most important optimized operating methods, constituting a benchmark of user satisfaction.

The author found that it is possible to design and build a VR-based furniture demonstration system with a good level of usability when a suitable quality design method is applied. The optimized user interaction indicators and implementation experience for the VR-based product demonstration presented in this study will be of use in further design and development of similar systems.

The purpose of this paper is to examine and discuss the responses and strategies firms use in relation to their supply base when dealing with current trends in the business landscape, and the different options that they have.

The paper draws on case study research of a company within the international health care sector to illustrate the relationship between trends, supply base characteristics and supply base strategies.

The paper presents a framework for a systematic approach that companies can use to develop supply base strategies. The framework illustrates that developing supply base strategies is a dynamic process that not only involves individual actions by the buying company, but also requires close interaction with suppliers.

Previous literature has not specified how different trends affect a company’s supply base in terms of increased complexity and (inter)dependence, and which supply base strategies companies use and the options that they have. The research presented here contributes to fill this void.

The purpose of this paper is to consider how product characteristics, segment differences, and brand‐name effects determine the price structure of the new car market.

The authors design and implement a hedonic price model that includes functional characteristics and addresses segment and brand heterogeneity.

The application of the model to an extensive dataset supports the hypotheses of segment differences and brand‐name effects. In mainstream segments automobile prices are determined more completely by functional characteristics. In high‐end segments carmakers follow implicit premium pricing strategies. The brand‐name effects reflect the incremental value added to a car by its brand name. Prestige brands not only earn brand‐name premia but also seize high‐margin market segments.

Several issues await investigation including possible discrepancies between the primary and secondary market, inter‐temporal change, and differences in attribute value across segments and marques.

The study has clear implications for auto manufactures, distributors and advertisers. It demonstrates the role of brands, segments, and observed product differences in the price structure of the automobile market. The proposed approach also allows managers to appraise new concepts and determine market‐driven prices.

The paper provides new interesting insights into critical issues for pricing strategy and brand management. It demonstrates the return on investment in brand building and identifies considerable opportunities for future research.

Customer support, such as equipment maintenance and repair, is an essential element in the successful marketing of a wide range of products, from computer systems to domestic appliances. Consequently, companies need to establish and maintain appropriate channels for high‐quality customer support; either as a part of their own operations or through third parties. This paper describes an exploratory investigation of the distribution channels and customer support strategies of five manufacturing businesses, using case study methodology. The results show the key role that customer support plays in various industries and illustrate the types of decisions companies make on how to provide high‐quality support for their customers. These findings have implications for managers in all industries where customer support is important, as they provide insights on how different channels and strategies affect the quality and efficiency of customer support.

Reviews and critiques literal views of product comprehension which rely on recall of key product claims to measure “correct” comprehension. Presents a constructive view of comprehension where product comprehension is seen as the process of forming personal interpretations of a product′s self‐relevance. Promotional strategies should be designed to suggest, encourage, and facilitate personal interpretations of the self‐relevance and positive consequences of product use. Marketers can use protocol probing procedures to obtain feedback about the personal interpretations consumers form during product comprehension.

To be successful, a company has to capture the initiative in an industry from its competitors. The author offers a detailed prescription for getting and keeping the strategic initiative in the face of countermoves by your opponent.

The key control characteristics (KCCs) are very important to control dimensional quality of the final product. The purpose of this paper is to propose optimization algorithm and rules of design KCCs by optimizing KCCs of 2D and 3D workpieces based on equations and candidate locating points.

This paper analyzes optimization process of 2D and 3D rectangle workpieces based on equations and candidate locating points by using fruit fly optimization algorithm (FOA). For decreasing variables of the algorithm, the improved fruit fly optimization algorithm (IFOA) is presented. Moreover, the Euclidean norm of inverse Jacobian is used as the objective function of optimizing KCCs by comparing different objective functions. Finally, a case of side frame assembly is presented to illustrate design and optimization of KCCs through IFOA, and results show that the method proposed in this paper is efficient and precise.

The paper provides some reasonable conclusions for the design and optimization of KCCs.

This paper designs and optimizes KCCs of fixtures and parts to improve dimensional quality of the final product.