help customers assert their needs, define variations from base products, visualize their options and ... achieve design for mass customization (Tseng and Jiao,.
Design by Customers for Mass Customization Products Mitchell M. Tseng (2), Xuehong Du Department of Industrial Engineering and Engineering Management, The Hong Kong University of Science and Technology Received on January 9,1998
Abstract
Producing what customers need with near mass production efficiency, or Mass Customization, has become a major trend in industry. Effective definition of customer requirements is a pre-requisite for realizing mass customization. We propose "Design by Customers" as an approach for companies to communicate to customers about what the company can offer, to find out customer needs, to assist customers in making choices and to negotiate for agreements. In this paper, the design and manufacturing capabilities of a company are represented in a Product Family Architecture. Adaptive Conjoint Analysis is then applied to help customers assert their needs, define variations from base products, visualize their options and assess alternatives. Keywords:
product design, requirement
analysis, computer aided design
1. Introduction
Quality,in the sense of satisfying individual customers' needs, has become the major differentiating factor between products. It has become more accepted that customersare willing to pay more for products that cater totheirindividual size, taste, style, need, or expression.
customer choices with the capabilities of the company, and extending the philosophy of concurrent engineering (Kahaner and Lu, 1993) to sales and marketing in a evolutionary product life cycle. The goal is to find the best match between what a company can offer and what the customers' want and to develop the company's capabilities so that customers can be best served over time.
Mass Customization aims to meet individual customer needs with near mass production efficiency. Meeting customer requirements requires full understanding of the customers' value~ and preferences. In addition, it is important that custqlT!!3rs know what the company can offer, their possible options and the consequences of their choices, perhaps as cost and schedule implications.
Traditionally, in order to compete in the market, manufacturers followed the approach of design for customers(Weiler and Lu, 1997; Deitz, 1995), where the product creation process started out with anticipating customers'needs. Based on this anticipation, products andproduction systems were then developed. Given the dynamic changes of customers' needs and the competitiveenvironment within which most businesses haveto operate, this anticipation can be very difficult. Furthermore,the stake of new product investment and the cost of inventory have increased significantly in recent years. A mistake in predicting customer needs could translateinto millions of dollars in financial loss. On the otherhand, due to the advent of modern manufacturing systems and the availability of a more educated workforce,today we have more flexibility in design and productionsystems than we ever in the past. Thispaper reports an approach, Design by Customers, in whichdesign and manufacturing work together to create an environment wherein cl,!stomers can take a proactive rolein defining their needs and negotiating to meet their explicit and implicit requirements. It differs from the traditionalapproach by bringing the voice of customers intodesign and manufacturing (Clausing, 1994), linking
Annalsof the CIRP Vol. 47/1/1998
The structure of the Product Family Architecture (PFA) used in this paper to facilitate the design process and achieve design for mass customization (Tseng and Jiao, 1996, 1997) will be discussed in the first section. Based on PFA, two complementary processes are developed. One is the front-end customer interaction process for analyzing and matching customer needs and the other one is the back-end supporting process for improving the compatibility of the customer needs and corporate capabilities. The approach is illustrated with an example of designing power supplies. 2. PFA - Representation of a Company's Capabilities In essence, a PFA represents what a company can offer to customers in terms of various product variants or extensions that can be derived from the base product designs to satisfy a spectrum of customer needs (Tseng and Jiao, 1996; 1997). A well-designed PFA provides a generic architecture for product families. A product family is composed of a base product (BP) and building blocks that customize the base product. With a PFA, each individual product can be defined as having M attributes. Each attribute can include several levels; e.g., attribute m can be on anyone of Lm levels. Each individual product is an instantiated case of its product family. A successfully designed PFA is based on concurrent engineering, optimal commonality and modularity design. It consists of four major components, namely, building blocks, configuration rules, product line taxonomy, and economic evaluation.
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.
.
. .
Building blocks - Building blocks are the basic elements of a PFA. They form the basis for reusability and flexibility in constructing variant products. Products can be viewed as a superposition of a number of building blocks. In forming PFAs, the criteria for partitioning building blocks are (a) current and future customer needs, (b) repeatability in design and fulfillment, and (c) ease of configuration. Appropriate levels of granularity are reached through balancing the commonality and logistic costs.
Product line taxonomy -
A productlinetaxonomy
represents the patterns of product portfolios: interrelationships among product families, base products (BPs) and customization building blocks. It reflects a specific product strategy and business vision. Some of the building blocks are organized to form base products that provide common functions to satisfy certain market niches. Base products capture commonality for meeting a class of customer, hence maximizing repetitions. Thus, a finished product can be configured by first selecting a base product and then determining the additional building blocks needed. A product line taxonomy is also a primary communication medium between customers and the PFA. With the product line taxonomy, customers can visualize a set of building blocks that will potentially satisfy their individual needs.
Configuration rules - Final products are delivered to customers by assembling building blocks according to configuration rules. These rules include: (a) the compatibility of different building blocks such as interface issues between building blocks; (b) the mapping relationships between the customers' needs and design parameters. Economic evaluation - Because a PFA provides choices for customers, it is also important that customers are informed about the consequences of choices in terms of cost, schedule, and other intangible factors. Economic evaluation can be provided in the form of rules, equations, and tools to help customers to make the necessary trade off.
3. Conjoint Analysis
-ACQuisitionof Customer
Needs
Conjoint Analysis (CA) is a set of methods originally designed to measure consumer preferences by assessing the buyers' multi-attribute utility functions in marketing research (InteIliQuest, 1990). It assumes that a product could be described as vectors of M attributes, Z1, Z2, ,.., ZM. Each attribute can include several discrete levels. Attribute Zm can be on anyone of the lm levels, Zm1, Zm2, .." Zm Lm; m=1, .." M. The utility functions defined as (McCullagh, 1989): M Ur
L",
Uml
= Wm
1=\
*dml
.
x
rml
I 0 {
=
if attribute mison llh level; otherwise
(3)
Usually, a large number of attributes, discrete levels and their preference indices are required to define the preferred products from the in customer's interaction. As such, it may become impractical for a design process. There are several approaches to overcome this problem. Green and others (Green, et aI., 1991; IntelliQuest, 1990) have proposed Adaptive Conjoint Analysis to explore customers' utility with iterations. Customers are asked I rate the relative importance of the attributes and refine the tradeoffs between attributes in an interactive setting to compare a group of testing profiles. Other approaches, such as the Kano Diagram, the Analytic Hierarchy Process (AHP) and the response surface can also be applied to refine the utility value (Urban and Hauser, 1993).
By knowingthe utility function, Urnl' customerscan find the relative contribution of each attribute and to make necessary tradeoffs. The customers can make their designs final by maximizing their own personal value for the unit price they are spending. 4. Process for Desi9!! Qy Customers Design is a mapping between functional requirements and physical parameters, "Design by Customers" allows customers to express directly their own requirements and carry out the mapping process into the physical domain. "Design by Customers" does not give customers a free hand to design in a vacuum. Instead, the process of Design by Customers guides customers to navigate through the capabilities of a company and define the best alternative that can meet the cost, schedule and functional requirements of the customers. Fig. 1 illustrates the process for Design by Customers on a PFA platform. Arrows represent data flows, ovals represent processes, and letters in uppercase without subscript represent a set of the relevant variables. The design process consists of two phases: the customer needs an acquisition phase and a product design. phase, There are two actors in the scenario: one is the customer, the other is the system that is supported by the PFA.
Phase I: Customer Needs Acquisition
.
(1)
(2)
the importance of attribute Zm for the customer. drml is the desirability for Ith level of attribute m, 1=1, ..., Lm;
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level of an attribute is selected or not. It can be expressed
as:
m=l 1=\
Uris the customer's utility for profile r, r=1, ..., R. Wmis
m's I-th level.
is a dummyvariabledenotingwhetherthe particular
Xrml
MLm
=2:Wm(2:dmIXrml) =2:2:UmIXrml m=\
are
m=1, ..., M. U rnl is the utility of attribute
.
Capability presentation In order to make informed decisions, customers are first informed of the capabilities of the company, including the spectrum of product offerings, product attributes, the possible levels of those attributes, and the organization of those levels. Here, the PFA provides a systematic protocol for customers to explore design options, Self-explication Customers are then asked to prioritize desired attributes for their requirements according to their concern about the difference. The
Customer Interaction
Supporting Process
-'--"'\
\
\\
PFt
\
Z, U(O)
U(I)
1. calculate U; ~-'-", 2. construct alternatives; ) 3. calculate utilities
i i
~ Product
z, U BP
Z,U
Platform Arch itectu re
L'1z(O)
Z + f1Z, U+f1U
Z ,f1Z BP+f1BP
Final design
Fig. 1: Process for Design by Customers
customers must assess the value they attach to each attribute and then specify their degree of relative preference between the most desirable and the least desirable levels. The results of this assessment are a set of Wm reflecting the relative importance attribute.
.
Utility exploration -
of each
Based on Wm,the next task
is to find a set of d~~ that reflect the desirability of each attribute level. The response surface can be applied here to create a set of testing profiles to search for those values. AHP can be used to estimate d;~~. Substituting Wmand d;~~ in (2), the utility of each attribute level is derived.
utility will be recalculated, until the customer gets a satisfactory solution.
.
Documentation After being confirmed by the customers, the design will be delivered. The design results will have refined Z and ~Z, and customized design BP and ~BP. These will be documented for the continuous evolvement of PFA.
Over time, the product family architecture can be updated so that prospective customers can be better served. This includes changes not only in the offerings of product families but also in production capabilities so that the capabilities of a company can be better focused to the needs of its customers.
PhaseII: Product Design
5. An ExamQle
.
Power supplies are necessary components of all electronic products. Because of diverse requirements, power supply products often are customized (Maurice, 1993) An example to illustrate the design process is as follows:
Preliminary design - With d:::'iand Wm, u~~)can be calculated with (1). Base products (BP) with a utility value close to U~~) are selected. Base product selection can be further fine-tuned through iterative refinement of U ml .
.
Customization Customers can modify the attributes Z to Z+~Z with the customization process of adding building blocks. Z will be adjusted, and the
A. Efficiency, reliability, price, noise, and size are the attributes important to the customer. Z(0)={Z1, Z2, Z3, Z4, Z5}. The levels of each attribute are shown in Table 1. Z11=70%, Z12=80%, Z13=88%, Z21=260khrs, Z22=330khrs, and so on.
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1,
Table 1: Significant Attributes of Power Supply
Attribute Efficiency (%) Reliability (MTBF: khrs) Price ($IW) Noise (p-p mv) Size (W/inch;1)
Level 76,80,88 260,330,760,840 1.0,2.7,4.5 50, 100 15,27,50
B. The customer rates the importance of the difference of the most desirable level verses the least desirable one.
C. During the customer needs acquisition phase, the customer's utilities are derived. They are depicted in Fig. 2. Reliability is the most significant factor affecting this customer's utility. It is followed by price, efficiency, and noise. The customer cares about the size of the power supply least. Thus, in order to maximize the customer's utility, effort should be put into improving the reliability rather than into reducing the size. The slope of a partworth line reflects the marginal utility for the customer. It is the benefit of elevating a particular attribute from one level to another in terms of customer utility.
(C I'-
00 00
0 0
...-
Table 2: Product Designed by Customer
Reliability (MTBF: hrs) Efficiency ('Yo) Noise (p-p vm) Size (W/inch;1) Price ($IW) -.... . . Utility
BPI 840 80 50 27 3.7 211
BPII 840 88 50 50 4.2 244
CP 760 80 100 27 2.5 256
D. The system recommends base products according to the refined utilities of the customer. In Table 2, BPI and BPII are the recommended base products. CP is the customized product designed after adjusting the attributes according to the customer. The prices are estimated here as well. BPI has the best performance and higher price, and CP provides the highest utility to the customer.
6. Conclusion A Design-by-Customers approach was developed for Mass Customization. By applying Adaptive Conjoint
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Analysis, customers can navigate through product families and define their preferences and hence design the products in the sense that they may map their own functional requirements into a physjcaJ domain on their own. This does not reduce importance of technology in the product design and delivery process. Instead, the technical challenge has been shifted to the preparation and presentation of product families so that the customers can make the best informed decisions for selecting the individual product to fulfill their own needs.A well designed Product Family Architecture provides the foundation for coordinating design, manufacturing, sales, marketing and logistic capability. In essence, product marketing and design engineering is coordinated through use of Product Family Architecture. With a systematic method, the possibility of applying computer-aided tools becomes feasible. An example with electronic power supply was used to test this approach, but the limitation and potential of this new approach remain to be further investigated. References
(1) Clausing, D., 1994, Total Quality Development: A Step by Step Guide to World-Class Concurrent EnQineerinQ,ASME Press (2) Deitz, D., 1995, Customer-driven Product Delivery, Mechanical Engineering, Dec.: 72-77 (3) Green, P.E., Krieger, A.M., Agarwal, M.K., 1991, Adaptive Conjoint Analysis: Some Cavates and Suggestions, Journal of Marketing Research, 28(2): 215-222 (4) IntelliQuest. American Marketing Association. Market Research Division 1990, Conjoint Analysis: A Guide for Designing and Integrating Conjoint Studies, Marketing Research Technique Series, Texas (5) Kahaner, D., and Lu, S., 1993, First CIRP International Workshop on Concurrent Engineering for Product Realization, Concurrent Engineering Research in Review, 5: 6-14 (6) Maurice K., 1993, Trends in AC/DC Switching Power Supplies and DC/DC Converters, IEEE (7) McCullagh, P., Neider, JA, 1989, Generalized Linear Models (2nd Edition), Chapman and Hall (8) Pine II, B. J. 1993, The New Frontier in Business \ Competition, Harvard Business School Press (9) Tseng, M.M., Jiao, J., 1996, Design for Mass Customization, CIRP Annals, 45: 153-156 (10) Tseng, M.M., Jiao, J., 1997, A variant Approach to Product Definition by Recognizing Functional Requirement Patterns, Journal of Engineering Design, 8: 329-340 (11) Urban, G.L., Hauser, JR, 1993, DesiQn And MarketinQ of New Products, 2nd Edition, Prentice Hall (12) Weiler, M.M., Lu, S.C-Y., 1997. Maximize Customer Satisfaction in a Product Design Process by Using Engineering Design as Collaborative Negotiation (ECN) Paradigm and The Dynamic Negotiation Model (DNM), ProceedinQs of CIRP International DesiQn Seminar: Multimedia TechnoloQY for Cooperative DesiQn and Manufacture, USC, Los Angeles, CA, USA, Oct., 1997: 29-36
