Robust Product Family Consolidation and Selection Using the Hypothetical Equivalents and Inequivalents Method

Author(s):  
Bryan R. Dolan ◽  
Kemper E. Lewis

The design and development of effective product lines is a challenge in modern industry. Companies must balance diverse product families that satisfy wide ranging customer demands with practical business needs such as combining manufacturing processes and using similar materials, for example. In this paper, the issue of consolidating an existing product family is addressed. Specifically, the Hypothetical Equivalents and Inequivalents Method (HEIM) is utilized in order to select an optimal product family configuration. In previous uses, HEIM has been shown to assist a decision maker in selecting one concept from a set when concept attributes conflict with each other. In this extension of HEIM, the optimization problem’s constraints are formulated using two different value functions, and common solutions are identified in order to select an optimal family of staplers. The result is then compared with the result found using a multi-attribute utility theory (MAUT) based approach. While each method has its advantages and disadvantages, and MAUT provides a necessary first step for product family consolidation and selection, a robust solution is achieved through HEIM.

2005 ◽  
Vol 128 (4) ◽  
pp. 659-667 ◽  
Author(s):  
Zhihuang Dai ◽  
Michael J. Scott

The development of product families, groups of products that share a common platform, is one way to provide product variety while keeping design and production costs low. The design of a product platform can be formulated as a multicriteria optimization problem in which the performances of individual products trade off against each other and against the objective of platform standardization. The problem is often solved in two stages: one to determine the values of the shared platform variables and a second to optimize the product family members with respect to specific targets. In the first stage, it is common to target the mean and variability of performance when fixing the values of platform variables. This paper contributes three new methods for platform development. The new methods are demonstrated on an electric motor example from the platform design literature, and the results are compared to those from existing methods. First, a preference aggregation method is applied to aggregate the multiple objectives into a single overall objective function. On the example problem, this approach gives superior results to existing techniques. Second, an alternative method that targets the minimum and maximum of the range of performance across the platform, instead of the mean and standard deviation, is proposed and shown to succeed where the existing method may fail. Third, a single-stage optimization approach which solves for both platform and nonplatform variables in a single pass is presented. This method delivers notably superior performance on the example problem but will, in general, incur greater computational expense.


Author(s):  
Aida Khajavirad ◽  
Jeremy J. Michalek

One critical aim of product family design is to offer distinct variants that attract a variety of market segments while maximizing the number of common parts to reduce manufacturing cost. Several indices have been developed for measuring the degree of commonality in existing product lines to compare product families or assess improvement of a redesign. In the product family optimization literature, commonality metrics are used to define the multi-objective tradeoff between commonality and individual variant performance. These metrics for optimization differ from indices in the first group: While the optimization metrics provide desirable computational properties, they generally lack the desirable properties of indices intended to act as appropriate proxies for the benefits of commonality, such as reduced tooling and supply chain costs. In this paper, we propose a method for computing the commonality index introduced by Martin and Ishii using the available input data for any product family without predefined configuration. The proposed method for computing the commonality index, which was originally defined for binary formulations (common / not common), is relaxed to the continuous space in order to solve the discrete problem with a series of continuous relaxations, and the effect of relaxation on the metric behavior is investigated. Several relaxation formulations are examined, and a new function with desirable properties is introduced and compared with prior formulations. The new properties of the proposed metric enable development of an efficient and robust single-stage gradient-based optimization of the joint product family platform selection and design problem, which is examined in a companion paper.


Author(s):  
Yiyang Zhang ◽  
Jianxin Jiao

To compete in the marketplace, manufacturers have been seeking for expansion of their product lines by providing product families. Product family positioning aims at planning the appropriate products to be provided to the target market segments. Due to the involved complexity such as diverse customer preferences, engineering costs, competition among similar products, etc, positioning the product family is very difficult. This paper proposes a shared surplus model for product family positioning. A comprehensive methodology for product family positioning is developed. An application of the proposed methodology for the notebook computer family positioning is reported.


2020 ◽  
Vol 11 (1) ◽  
pp. 241
Author(s):  
Juliane Kuhl ◽  
Andreas Ding ◽  
Ngoc Tuan Ngo ◽  
Andres Braschkat ◽  
Jens Fiehler ◽  
...  

Personalized medical devices adapted to the anatomy of the individual promise greater treatment success for patients, thus increasing the individual value of the product. In order to cater to individual adaptations, however, medical device companies need to be able to handle a wide range of internal processes and components. These are here referred to collectively as the personalization workload. Consequently, support is required in order to evaluate how best to target product personalization. Since the approaches presented in the literature are not able to sufficiently meet this demand, this paper introduces a new method that can be used to define an appropriate variety level for a product family taking into account standardized, variant, and personalized attributes. The new method enables the identification and evaluation of personalizable attributes within an existing product family. The method is based on established steps and tools from the field of variant-oriented product design, and is applied using a flow diverter—an implant for the treatment of aneurysm diseases—as an example product. The personalization relevance and adaptation workload for the product characteristics that constitute the differentiating product properties were analyzed and compared in order to determine a tradeoff between customer value and personalization workload. This will consequently help companies to employ targeted, deliberate personalization when designing their product families by enabling them to factor variety-induced complexity and customer value into their thinking at an early stage, thus allowing them to critically evaluate a personalization project.


2021 ◽  
Vol 11 (3) ◽  
pp. 965
Author(s):  
Irina Stipanovic ◽  
Zaharah Allah Bukhsh ◽  
Cormac Reale ◽  
Kenneth Gavin

Aged earthworks constitute a major proportion of European rail infrastructures, the replacement and remediation of which poses a serious problem. Considering the scale of the networks involved, it is infeasible both in terms of track downtime and money to replace all of these assets. It is, therefore, imperative to develop a rational means of managing slope infrastructure to determine the best use of available resources and plan maintenance in order of criticality. To do so, it is necessary to not just consider the structural performance of the asset but also to consider the safety and security of its users, the socioeconomic impact of remediation/failure and the relative importance of the asset to the network. This paper addresses this by looking at maintenance planning on a network level using multi-attribute utility theory (MAUT). MAUT is a methodology that allows one to balance the priorities of different objectives in a harmonious fashion allowing for a holistic means of ranking assets and, subsequently, a rational means of investing in maintenance. In this situation, three different attributes are considered when examining the utility of different maintenance options, namely availability (the user cost), economy (the financial implications) and structural reliability (the structural performance and subsequent safety of the structure). The main impact of this paper is to showcase that network maintenance planning can be carried out proactively in a manner that is balanced against the needs of the organization.


2018 ◽  
Vol 10 (10) ◽  
pp. 3453 ◽  
Author(s):  
Jiyong Ding ◽  
Juefang Cai ◽  
Guangxiang Guo ◽  
Chen Chen

With the rapid development of the urbanization process, rainstorm water-logging events occur more frequently in big cities in China, which causes great impact on urban traffic safety and brings about severe economic losses. Water-logging has become a hot issue of widespread concern in China. As one kind of natural disasters and emergencies, rainstorm water-logging has the uncertainties of occurrence, development, and evolution. Thus, the emergency decision-making in rainstorm water-logging should be carried out in stages according to its development trend, which is very complicated. In this paper, an emergency decision-making method was proposed for urban water-logging with a hybrid use of dynamic network game technology, Bayesian analysis, and multi-attribute utility theory. The dynamic game process between “rainstorm water-logging” and “decision-making group” was established and the dynamic generation of emergency schemes was analyzed based on Bayesian analysis in various stages of water-logging. In terms of decision-making attributes, this paper mainly considered two goals, i.e., ensuring smooth traffic and controlling emergency cost. The multi-attribute utility theory was used to select the final scheme. An example analysis in Guangzhou of China showed that the method is more targeted and can achieve emergency management objectives more effectively when compared with traditional methods. Therefore, it can provide reference for the scientific decision-making of emergency management in urban rainstorm water-logging.


Author(s):  
Muhammad L O Mardin ◽  
Achamad Fuad ◽  
Hairil K Sirajuddin

Abstrak: Banyaknya pilihan rumah seringkali membuat calon pembeli merasa ragu atau kesulitan saat harus menentukan langsung rumah yang mana yang akan dibeli, karena pada pemilihan perumahan yang akan dibeli belum ada sistem yang akan membantu dalam memilih perumahan yang dibeli, sehingga pada proses pemilihan masih menggunakan pikiran saja dan belum ada perhitungan pada saat pemilihan perumahan yang akan di beli. Tujuan penelitian ini menghasilkan sebuah sistem pendukung keputusan pemilihan perumahan. Kriteria yang diajukan dalam proses pemilihan perumahan yaitu: Harga perumahan, Jarak dari pusat kota, Jarak dengan pasar terdekat, [1], tipe perumahan, jarak dengan jalan umum, jarak dengan lahar. Dari hasil pemilihan perumahan menggunakan sistem yang telah dibuat. dengan 10 alternatif, dengan tingkat kepentingan masing-masing kriteria yang digunakan yaitu: harga = 5, tipe rumah = 5, jarak dengan pusat kota = 2, jarak dengan pasar terdekat = 2, jarak dengan jalan umum = 4, jarak perumahan dengan lahar = 5, telah diperoleh alternatif yang akan direkomendasikan yaitu perumahan safira residen 70 dengan dengan nilai tertinggi 0,65.Kata kunci: Sistem Pendukung Keputusan, Pemilihan, Perumahan, Multi Attribute Utility TheoryAbstract: A large number of choices of houses often makes prospective buyers feel doubtful or difficult when they have to determine directly which house to buy because, in the selection of housing to be purchased, no system will assist in choosing the housing to be purchased so that in the selection process, you still use your mind. There is no calculation at the time of the selection of housing to be purchased. The purpose of this research is to produce a housing selection decision support system. The criteria proposed in the housing selection process are housing prices, distance from the city, distance to the nearest market, [1], type of housing, distance to public roads, distance to lava. From the results of the election using the system that has been created. With ten alternatives, with their respective interests. The criteria used are: price =5, type of house = 5, distance to city center = 2, distance to the nearest market = 2, distance to public roads = 4 distance from housing to lava = 5, has obtained an alternative that will be recommended, namely the residential sapphire housing 70 with the highest value of 0.65Keywords: Housing, Selection, Decision Support System, Multi-Attribute Utility Theory.


Telematika ◽  
2020 ◽  
Vol 17 (1) ◽  
pp. 26
Author(s):  
Afif Irfan Abdurrahman ◽  
Bambang Yuwono ◽  
Yuli Fauziah

Flood disaster is a dangerous disaster, an event that occurs due to overflow of water resulting in submerged land is called a flood disaster. Almost every year Bantul Regency is affected by floods due to high rainfall. The flood disaster that struck in Bantul Regency made the Bantul District Disaster Management Agency (BPBD) difficult to handle so that it needed a mapping of the level of the impact of the flood disaster to minimize the occurrence of floods and provide information to the public.This study will create a system to map the level of impact of floods in Bantul Regency with a decision support method namely Multi Attribute Utility Theory (MAUT). The MAUT method stage in determining the level of impact of flood disasters through the process of normalization and matrix multiplication. The method helps in determining the areas affected by floods, by managing the Indonesian Disaster Information Data (DIBI). The data managed is data on criteria for the death toll, lost victims, damage to houses, damage to public facilities, and damage to roads. Each criteria data has a value that can be used to determine the level of impact of a flood disaster. The stages for determining the level of impact of a disaster require a weighting calculation process. The results of the weighting process display the scoring value which has a value of 1 = low, 2 = moderate, 3 = high. To assist in determining the affected areas using the matrix normalization and multiplication process the process is the application of the Multi Attribute Utility Theory (MAUT) method.This study resulted in a mapping of the level of impact displayed on google maps. The map view shows the affected area points and the level of impact of the flood disaster in Bantul Regency. The mapping produced from the DIBI data in 2017 produced the highest affected area in the Imogiri sub-district. The results of testing the data can be concluded that the results of this study have an accuracy rate of 95% when compared with the results of the mapping previously carried out by BPBD Bantul Regency. The difference in the level of accuracy is because the criteria data used are not the same as the criteria data used by BPBD in Bantul Regency so that the accuracy rate is 95%.


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