Number Of Product Variants Research Articles

Assessment of Product Variety Complexity

Product variety complexity assessment plays a vital role in system design, as it has tremendous negative effects on manufacturing complexity in assembly systems and supply chains. On the other hand, practitioners and researchers frequently consider the number of product variants as a sufficient measure to be used to manage this kind of complexity. However, as shown in this study, such a measure does not reflect all pertinent features of complexity. Therefore, the main goal of the paper is to develop a measurement method for product variety complexity that adequately reflects relevant relations between the portfolio of optional components and the number of product variants. As presented in the paper, the concept of information theory can be effectively applied to measure product variety complexity. Moreover, such a measure can also be useful to better understand this system's properties in order to reduce the level of variety-induced complexity. As such, the proposed method can be viewed as a complementary tool for reducing manufacturing complexity in terms of mass customization. The developed complexity metric was successfully tested on a realistic design example.

Towards a mass customization in the fashion industry: An evolutionary decision aid model for apparel product platform design and optimization

To meet the diverse needs of customers with a competitive offering, many companies are utilizing product families and platform-based product development to increase variety, shorten lead times and reduce costs. However, current research in this area does not sufficiently examine broader enterprise considerations, such as production and inventory management complexity and costs, or expected sales. Furthermore, very few existing platform design methods integrate fitting and ergonomic considerations in their formulation.This study proposes a two-stage platform-based design process to support apparel brands to implement mass customization (MC) strategies. This work has been conducted in collaboration with Yamamay, an Italian underwear and lingerie brand. In the first stage, the characteristics of a scale-based platform (i.e. the number of product variants) are determined based on (i) the results of the anthropometric analysis of a large Italian female population sample, (ii) business considerations discussed together with brand managers and experts, (iii) and benchmarking data. In the second stage, a novel and ad-hoc developed evolutionary-based decision aid model stretches and shrinks the resulting classes looking for the optimal trade-off based on anthropometric data between the demand of garments that fit well and the percentage of the population that is satisfied with the proposed product family.The approach proposed here has been proved effective not only in theory but also in practice through a pilot launch of a test product family. Integrating scale-based platform design of apparel with ergonomic, production, inventory, and sales considerations makes this study unique and paves the way for the implementation of customization-as-a-service business model and for the transformation of the fashion industry into a technology- and knowledge-intensive industry.

Measurement of Food Losses in a Hungarian Dairy Processing Plant.

The phenomenon of food waste and food loss at any stage of the supply chain is significant in developed economies. The purpose of this article is to highlight the areas of milk processing where milk loss occurs, and, after quantifying the data obtained, reveal the extent of the losses. To achieve the goals, we conducted on-site visits to one of Hungary’s milk processors. The methodology is based on the Food Loss and Waste (FLW) standard, accordingly we determined the extent of milk loss at the company level, supplemented with loss values by each dairy product. During the analyzed processing stages (receiving of raw milk, skimming, pasteurization, Extended Shelf-Life (ESL) milk, cheese milk, sour cream, yoghurt, and kefir) 1203.4–1406.8 L of raw material per day can be accounted as losses, which makes up 0.9–1% of daily production. A Milk Production-Milk Losses (MPML) model was created where six factors (technology and automation, design of the plant aspects, quantity of orders, expertise of employees, number of product variants, optimal storage capacity) were methodized that significantly influence the rate of milk losses over different time periods. Our paper highlights how areas of the production stage can be developed to decrease milk loss.

Implementation of Lean Manufacturing to Reduce the Delivery Time of a Replacement Part to Dealers: A Case Study

In today’s automotive industry, Lean production systems are used successfully to reduce delivery times. The current case study addresses a problem that affects an automotive company, which is the excessive delivery time of a spare part to its both national and international authorized dealers. In order to reduce the delivery time of this replacement part, the Lean Manufacturing methodology was used. For this purpose, the value stream mapping and the proposed A3 report are the tools used. With the use of these tools, activities that did not add any value are eliminated or modified; in addition, the logistical flow of the modules of the door-side trim panel delivery process is improved. As a result, added value is increased, the delivery time is reduced (for Mexico) and the number of product variants is reduced. Now, the painting process is done by the authorized dealers, and the number of pieces used for every spare part was estimated. The study demonstrates that the integration of value stream mapping administrative/productive in conjunction with the A3 report proposal allows to identify and eliminate waste in the delivery process.

The evolution of molds in manufacturing: from rigid to flexible

Abstract Nowadays, dynamic products life cycles and increase in the number of product variants have led to reduction in demand per variant. This modern trend is in contrast with the high production volume of manufacturing processes such as injection molding, since they are commonly employed for mass production due to their long changeover time. Traditional rigid molds do not seem to be able to cope with the current industrial and market challenges. Flexible and reconfigurable molding processes, such as the discrete pin tooling systems and changeable molds, appear to be a promising choice for achieving manufacturing economic sustainability. They represent an effective way to save resources and reduce labor costs and setup times. This paper explores the evolution of molds used in manufacturing, from the old models to the current reconfigurable ones through a state-of-the-art analysis of academic research and solutions implemented by industry. Conclusions and insights are presented.

A Fixture Design Retrieving Method Based on Constrained Maximum Common Subgraph

Fixtures are widely used in almost any modern manufacturing. They add directly to the cost base, impact manufacturing firms’ responsiveness and contribute to the overall product quality. Computer-aided intelligent fixture design was developed over the years to give a competitive edge to the manufacturing firms who are facing unprecedented competition and challenges. Among the techniques, case-based reasoning (CBR) method leverages previous design experience and emerged as one of the most popular methods. However, existing CBR methods are more focused on frame work building and less on detailed techniques on case retrieving, which is the central part of any CBR methods. This would inevitably impose negative impact on the overall efficiency of any CBR-based methods. In light of this, this paper presents a new case retrieving method based on a constrained common subgraph technique. This technique tracks down similar cases from a case library through comparing the maximal common subgraphs constrained by meeting fixturing functional requirement. Efficient and robust algorithms have been developed subsequently to implement this technique. The developed method can be highly effective for retrieving cases related to some manufacturing parts with complex geometry. An illustrative example, combined with other key fixture design factors, demonstrates the effectiveness of the proposed method. The presented method is intuitive and can be used in combination with existing CBR methods and well positioned for the upcoming “big data” manufacturing. Note to Practitioners —Providing capability for rapid responsiveness, enhancement of product quality, and production at low cost are the three main objectives for the wide manufacturing firms. Fixtures are widely used across manufacturing and assembly processes, and they are closely linked to all these three objectives. Today’s manufacturing enterprises face unprecedented challenges to control costs and to deal with an ever increasing number of product variants and smaller lot sizes. All these facts raise high demands on computer-aided intelligent fixture design. Case-based reasoning (CBR) method, tackling new problem by using the solution of similar past problems or through revising the previous solution, gains popularity among researchers and practitioners. However, existing CBR methods put more focus on CBR framework design while the case retrieving, the key process of any CBR methods, still relies on some basic feature attributes comparison. This would inevitably reduce the overall effectiveness of the CBR method. In view of that, this paper proposed a graph method for case retrieval based on comparing maximal common subgraphs (MCSs). Dictated by fixture functional requirement, a constraint (to match machining features and/or other user defined requirement) has been imposed during the MCS search process. This constraint turns out to be quite useful in term of reducing search space and increasing computation efficiency. Robust algorithms have been subsequently developed to implement this technique. Graph is a powerful tool to analyze structured object, the proposed method can handle some bespoke and complex fixture design cases. The presented method is intuitive and flexible and can be integrated into existing CBR frameworks to improve the allover effectiveness of current intelligent fixture design.

Simulation investigational method for intermittent production systems

Nowadays, production system process improvement is going through sweeping changes. The trends include an increase in the number of product variants to be produced, as well as the reduction of the production’s lead time. These trends were induced by new devices of the industry’s 4.0, namely the Internet of Things and cyber physical systems. The companies have been applying intermittent production systems (job production, batch production) in increasing number because of the increase in the number of product variants. Consequently, increasing the efficiency of these systems has become especially important. The aim of development in the long term – not achievable in many cases – is the realisation of unique production with mass production’s productivity and specific cost. The improvement of complex production systems can be realized efficiently only through simulation modeling. The intermittent production systems’ standardized simulation investigational method has not elaborated so far. In this paper I will introduce a simulation investigational method conception for complex system improvement and also present a practical example in connection with the elaborated method.<br>

Augmenting feature model through customer preference mining by hybrid sentiment analysis

We use sentiment analysis of online product reviewers to extract customer preference information.The proposed sentiment analysis method is a hybrid combination of various affective lexicons.We adopt the commented features from product users to enhance the basic feature.We incorporate the customer preference information as attribute into the model.We demonstrate the feasibility and potential of the proposed method via an application case. A feature model is an essential tool to identify variability and commonality within a product line of an enterprise, assisting stakeholders to configure product lines and to discover opportunities for reuse. However, the number of product variants needed to satisfy individual customer needs is still an open question, as feature models do not incorporate any direct customer preference information. In this paper, we propose to incorporate customer preference information into feature models using sentiment analysis of user-generated online product reviews. The proposed sentiment analysis method is a hybrid combination of affective lexicons and a rough-set technique. It is able to predict sentence sentiments for individual product features with acceptable accuracy, and thus augment a feature model by integrating positive and negative opinions of the customers. Such opinionated customer preference information is regarded as one attribute of the features, which helps to decide the number of variants needed within a product line. Finally, we demonstrate the feasibility and potential of the proposed method via an application case of Kindle Fire HD tablets.

Social Media and Product Line Design

It is common for consumers to rely on opinion leaders, who presumably have a higher expertise in the product category, to form beliefs about the product quality. At the same time, the evaluations and product adoptions of opinion leaders are influenced both by the product quality and by their idiosyncratic preferences (fit). When opinion leaders do not provide a very detailed review, their followers need to form expectations of how much the opinion leader's recommendation is driven by product quality and how much it is driven by an idiosyncratic fit of the product to the opinion leader. This paper considers how the firm should adjust its optimal choice of the product variety in the presence of word of mouth, given that the opinion leader is likely to have more expertise and therefore, be better able to choose the version of the product that fits her best. It shows that while the opinion leader's presence may be a force toward either an increased or decreased number of variants, generally speaking, the distortion is upward if it is more difficult to satisfy the opinion leaders, which could be either due to the higher importance of fit or due to their higher standards. We further show that the firm's knowledge of the true quality may increase the distortion of the number of product variants it offers even when the equilibrium number of variants is pooling across the product qualities.

A fuzzy optimisation method for product variety selection under uncertainty constraints

Nowadays, it is believed that increasing product variety could help manufacturing companies to increase sales volumes and gain more profits. An effective way that has been widely employed in industry is to implement product family strategy based on a modular architecture, with which a large number of product variants can be quickly generated using combinations of different alternative modules or components. However, it is not easy for a company to decide what product variants should be selected and produced in order to maximise profits. This is not only about marketing strategy but also tightly associated with the companies’ own uncertain manufacturing resource constraints. Therefore, in this paper, a fuzzy optimisation model is adopted for modelling the product variety selection problem based on an existing modular product family architecture while at the same time considering uncertain manufacturing resource constraints. The proposed method can help various manufacturing companies to select the best product variety under the uncertain market environment and limited manufacturing and supplying capacity. Finally, a hypothetical car’s selection is presented as an example to illustrate the effectiveness and feasibility of the method proposed in this paper.

Managing product variety through configuration of pre-assembled vanilla boxes using hierarchical clustering

Postponement strategy and platform-based production are common practices of mass customisation to address supply chain challenges due to the requirement of product variety. This paper focuses on implementing mass customisation through development of semi-finished forms of products (vanilla boxes) to reduce supply chain cost and facilitate the production process. The challenge is that the possible number of vanilla box configurations grows dramatically with the increase in number of product variants. In the solution approach, the basic information of product variety is captured in a matrix format, specifying the component requirements for each product variant. Then, hierarchical clustering is applied over the components with the considerations of demands. The clustering method consists of three major stages: similarity analysis, tree construction and tree-based analysis. The key stage is similarity analysis, in which problem-specific information can be incorporated in the clustering process. Two numerical examples from the literature are used to verify that the clustering approach can yield good-quality solutions.

Worker Information Systems: State of the Art and Guideline for Selection under Consideration of Company Specific Boundary Conditions

Due to customer specific products, the number of product variants and the complexity of assembly processes increase. To meet these challenges, worker information systems are used to manage information diversity in manual assembly and to provide the right information at the right time in a lean way. Such systems are available in various types and their classification depends on a particular point of view. In order to enable a holistic overview of the existing diversity, this paper summarizes such systems and their benefits. For this purpose, available categories are shown. Accordingly, this paper serves as a summarizing report for the state of the art. Furthermore, the implementation and configuration of worker information systems depend on company specific boundary conditions. Considering them, a guideline is presented for the selection of worker information systems.

A Game-Based Approach to Raise Quality Awareness in Ramp-Up Processes

Today's production systems are complex sociotechnical systems. Both technical challenges, as well as the integration of human employees with their diverse abilities, wants, and needs, must be considered. Due to a growing number of product variants, shorter lead times, and global supply chains, planning production systems is becoming increasingly difficult, both on the technical and human levels. The highly volatile and uncertain character of production systems is intensified by the growing complexity and need for results in shorter decision times for ramp-up management. To handle the increasing complexity, human decision makers must be adequately trained for the ramp-up period. Therefore, the influential factors and their magnitude from both the technical and the human perspective must be identified and understood. This knowledge can help to manage the complexity of ramp-up processes, reduce the disturbances within the processes, and strengthen their overall resilience against failures.To adequately understand the human and technical factors that relate to ramp-up processes, it's necessary to have an experimental framework. This framework should support the identification and quantification of sociotechnical factors, enabling practitioners and researchers to model suitable interventions. In this article, the authors propose, develop, and evaluate a business simulation game that serves as such an empirical framework. The game is furthermore suitable to train managers before the ramp-up process. The achieved performance in the business simulation game may be used to evaluate a person's suitability for the task and to identify individual training potential.

Product feature and functionality driven integrated framework for product commercialization in presence of qualitative consumer reviews

The purpose of this research is to aid manufacturers operating in multiple market segments (characterised by a number of product variants) to formulate and synchronise their product commercialisation strategy. Product commercialisation is primarily characterised by upgrading/launching product features aimed at meeting customer’s preferences, while at the same time, enabling the enterprise to achieve its major commercial objectives. Firstly, by employing the semi-automated crowd sourcing-based approach and considering qualitative customer evaluations, customer-preferred product features have been identified and their relative weights determined. Thereafter, a detailed mixed integer quadratic programming formulation has been evolved taking into account pertinent commercial objectives of the enterprise and engineering-level constraints of the product. The developed formulation has been solved using the Branch and Cut method of commercial solver, LINGO. Detailed sensitivity analysis has been carried out, followed by populating key managerial insights. The proposed framework has been illustrated using a real-life case example of operator cabin used in heavy construction equipment industry. Our focus has been on development and illustration of devised framework; hence, the superiority of results has not been claimed. Better results may be obtained using other heuristics/algorithms.

Scenario-Based Determination of Alternative Product Architecture Designs

Today many producing companies face two major challenges: they have to maintain a high degree of product differentiation whilst reducing costs through economies of scale. One way to face these challenges is the development of modular product architectures that allow to produce a number of product variants and product generations using one single architecture. The complexity for the product development has thereby increased since expected future changes in products have to be anticipated in the designing process to minimize modification costs. The more robust a product architecture is regarding future changes, the longer an architecture can be used which directly translates into economic advantages for the company. Most companies though struggle to apply the required processes and tools to develop scenario-robust product architectures for their portfolio. This paper aims at the presentation of a methodology to develop alternative, scenario-robust product architecture designs.

Configuration of Assembly Supply Chain Using Hierarchical Cluster Analysis

The purpose of this paper is to propose a clustering method that configures assembly supply chains. In mass customization, product variety is often characterized by a modular product structure, in which each module may offer several variants to deliver product variants. In this context, assembly supply chain is referred to a network of suppliers who produce and assemble product variants. Given that the proportion of the product variants is specified, the technical problem is how to configure the structure of the assembly supply chain in order to reduce the complexity incurred by product variety. The technical challenge is that the possible number of configurations grows dramatically with the number of product variants. Also, enumerating the possible configurations in a mathematical framework is not a trivial task. Instead of taking an exhaustive approach, the solution approach of this paper is based on hierarchical cluster analysis, in which the tree structure is applied to configure assembly supply chain. The core technique is to investigate the coupling concept in the context of assembly supply chain to characterize the grouping conditions in the structuring process. Few examples are utilized to demonstrate and verify the methodology.

A New Engineering Design Paradigm – The Quadruple Bottom Line

The number of product variants has increased dramatically in recent years. The increase in variety has a multitude of reasons including customers’ demand for new product functions and features, different regional requirements, and large number of market segments having different needs. The emergence of new materials and technologies make new and different product features possible, and the fierce competition among manufacturers and retailers to distinguish their products, attract more buyers and secure larger markets are important drivers of increased variety. Mass customization (MC) means producing goods and services to meet individual customer's needs with near mass production efficiency without compromising cost, quality or delivery. It aims at achieving economy of scope at a cost approaching that of economy of scale by delaying products differentiation and capitalizing on commonality and similarity between variants within a product family. Personalization means that products are made-to-measure or to customers’ personal specifications. However, to achieve some measures of economy, only few product components are allowed to be manufactured to fit the customer specifications.This paper discusses the evolution of product design for mass customization and personalization as well as product variety and complexity management in the context of engineering design and the changing design paradigms.The main objective of customization and personalization is to be competitive in the market and to maintain a good market share. This significant innovation has been based primarily on achieving the traditional objectives of the best quality product, produced for a competitive cost just in time to meet the market needs in a timely manner. Beyond customization and personalization for companies to sustain in the future, they must also meet the continuous innovation requirements while producing environmentally friendly products and the socio-technical objectives, hence meeting a quadruple bottom line.

Factors that catalyse, facilitate and motivate the decision to implement activity‐based costing in Jordanian industrial companies

PurposeIn spite of facilitating and motivating factors in the external environment, the implementation of new management‐accounting techniques as activity‐based costing (ABC) in companies is disappointing. The aim of the study is to determine factors that catalyse, facilitate and motivate the decision to implement ABC in Jordanian industrial companies. Additional objectives include determining the problems associated with ABC implementation and assessing the degree of success of ABC implementation in Jordan.Design/methodology/approachA sample of the Jordanian industrial companies was selected and a questionnaire survey was employed using a five‐point Likert scale to collect data from the financial managers, descriptive and analytical statistics were used to analyze the collected data.FindingsThe findings indicate that the most important factor that facilitates the decision to implement ABC was the provision of adequate training and the most influential factors which motivate the process of ABC implementation include an increasing proportion of overhead costs, and an increasing number of product variants. Consequently, this study found that the interaction of three types of factors (catalysts, facilitators and motivators) create the potential for change in these companies. Barriers to change could make the change process slower, hindering, and even preventing change; and barriers to change were identified that may explain the differing implementation rates of ABC in the Jordanian industrial sector. The greatest barrier to implementing ABC was found to be its high cost of implementation, followed by the high cost of ABC consultancy and computer staff time.Originality/valueThe study adds new elements to the institutional approach, and integrates it with concepts from psychology and organizational culture, to create a better understanding of management accounting. The results of study contribute to existing knowledge in the area of understanding the factors which act as catalysts, facilitate, and motivate ABC innovation and of those factors that create barriers to ABC implementation in Jordan.

On the evaluation of product customization strategies in a vertically differentiated market

This paper presents a formal approach to evaluate the value of enhancing product customization in a vertically differentiated market. Different from most existing studies that tend to associate the level of customization with the number of product variants, we take a rather different view to the level of customization which we define as the degree to which consumers are involved along the value chain. Consequently, a higher level of customization is achieved when consumers are involved further upstream in the chain. The novelty of our approach stems from the integration of both marketing- and production-related factors that enable us to: consider trade-offs between customization, lead times and manufacturing costs; and analyze how these trade-offs should be addressed in a market in which one group of consumers is highly concerned about product customization, whereas the other group is more concerned about lead time. Through numerical examples, we demonstrate how the interplay between marketing- and operation-related factors affects firm's decision on the most appropriate level of customization.

Modeling of Manufacturing Complexity in Mixed-Model Assembly Lines

Mixed-model assembly lines have been recognized as a major enabler to handle product variety. However, the assembly process becomes very complex when the number of product variants is high, which, in turn, may impact the system performance in terms of quality and productivity. This paper considers the variety induced manufacturing complexity in manual mixed-model assembly lines where operators have to make choices for various assembly activities. A complexity measure called “operator choice complexity” (OCC) is proposed to quantify human performance in making choices. The OCC takes an analytical form as an information-theoretic entropy measure of the average randomness in a choice process. Meanwhile, empirical evidences are provided to support the proposed complexity measure. Based on the OCC, models are developed to evaluate the complexity at each station and for the entire assembly line. Consequently, complexity can be minimized by making system design and operation decisions, such as error-proof strategies and assembly sequence planning.