Week 14 - Redesign Supply Chain Processes

Source / Reference:
1)"Product architecture assessment: a tool to link product, process, and supply chain design decisions" by 
Sebastian K. Fixson, Research in Journal of operations management [0272-6963] Fixson, Sebastian yr:2005 vol:23 iss:3-4 pg:345 -369 
http://www.sciencedirect.com.ezproxy.lb.polyu.edu.hk/science/article/pii/S027269630400110X


Subject:
Link business process, product and supply chain design decisions together


Motivation:


In the last lecture, Redesign Supply Chain Processes, the concepts of supply chain and redesigning process of supply chain are taught. Since supply chain is cross-organizational in nature, misalignments occur in e-process, information and knowledge. Therefore, redesigning the partner interface process (PIP) is a need to reduce misalignments in the supply chain process. However, the focus of reengineering the PIP is on the collaboration among enterprises, which may be rather passive in terms of the whole business process and product/service. How to link the business process, product and supply chain design decisions together in order to assess the relationship and have a better, more precise redesign is the motivation of this blog. 


Introduction
For many manufacturing firms, heightened competition has brought back into focus the value of considering manufacturing concerns during product design, and to overlap formerly sequential design processes. More recently, the competition has intensified for many firms through increased demand heterogeneity and shorter product life cycles. Formerly large mass markets have fractured into smaller niche markets demanding higher levels of product variety while competitors are introducing new products in shorter intervals. To respond to these pressures, many firms have put customization of mass produced products at the center of their attention.
A concept of “concurrent enterprising’ is addressed to describe the future direction of mass customization, to achieve an alliance of customers, products, processes, and logistics by means of parallelity, integration, standardization, teamwork, and many others, for delivering an increasing product variety to satisfy diverse customer needs while maintaining near mass production efficiency. A comprehensive product architecture assessment methodology can serve as the hub to link these decisions with each other.


Product architecture assessment
In order to achieve the ultimate goal to assess the impact of product architecture decisions on decisions in the domains of product, process, and supply chain, what is needed then is a method to determine where in between these extremes – modular and integral – a particular design is located in the space of possible function–component mappings, how two or more mappings compare to each other with respect to their locations in this space. The product architecture assessment framework combines the comprehensiveness of the conceptual models with the operationalizability of the engineering models and lays the foundation for mathematical models to be applied to individual aspects.


Dimension 1: function–component allocation scheme
To build on the definition that a characteristic feature of product architecture is the way in which functions are allocated to components requires a mechanism that determines and measures this dimension reliably. In other words, all three pieces of the function–component allocation scheme need a rule-based procedure to ensure repeatable results of function, component and the allocation scheme.


Dimension 2: interface characteristics
Products can exhibit different degrees of being coupled, depending on the product life cycle phase. The interface measurement needs to be conducted on a disaggregated level to allow investigation of the individual effects. To make the dimension interface measurable, the information are grouped into three categories: type, reversibility and standardization. In each category, the corresponding interface characteristic is assessed individually. Like the function–component allocation, the interface assessment investigates the characteristics of the interfaces only on the determined hierarchy level.


Link all things together: product architecture maps
Together with the function–component allocation data and the interface information completes the description of the product architecture, adding the information for all three interface dimensions to the function–component allocation map results in the product architecture map. These product architecture maps show in their x–y plane how the functions are allocated to the components. Independent from that, and independent of each other, the different interface dimensions are shown along the vertical axis (z). These product architecture maps serve as a graphic representation of the complete product architecture description. They allow quick visual references of similarities and differences of the analyzed product architectures. 

Product architecture change in the FCA scheme

Product architecture coordinates design decisions across process and product domains

Conclusion
Product architecture assessment is a multi-dimensional descriptive product architecture framework. This framework integrates insights from literature streams on new product development, operations management, and supply chain management. This framework can serve multiple purposes in management and research.
In practical, more information and linkage among the three aspects: process, product and supply chain are visualized through this assessment to assist in making decision. 

Week 13 - Process Redesign (3) and Implementation

Source / Reference:
1)"Pattern-based reasoning for rapid redesign: a proactive approach " by Li, Simon ; Chen, Li, Research in Engineering Design, 2010, Vol.21(1), pp.25-42
http://www.springerlink.com.ezproxy.lb.polyu.edu.hk/content/k523937104546118/


Subject:
Further development of Rapid Redesign model: a proactive approach


Motivation:

Refer to my previous blog: Other model of process redesign: Model-based Rapid Redesign, I further investigate more on his topic and I found another article that is written by the same author, which is a further development of the rapid design model. In the successive article, a proactive approach, Pattern-based reasoning for rapid redesign is discussed. This blog is to briefly introduce this new approach, compare it with the previous one and observe what have been improved.


Introduction
In the original approach - Pattern-based reasoning for rapid redesign, the decomposition process for redesign is not activated until the presence of a redesign request. This prior work represents a reactive approach where a new set of decomposition patterns should be generated in accordance with a different redesign request input.
In the new proactive approach, the decomposition patterns capturing generic decomposed structures of a given design model are created in advance and stored in a design library before any redesign request emerges. These pre-generated patterns are able to address any upcoming redesign request without further decomposition procedures in redesign. This proactive approach is developed in a new framework of pattern based reasoning that is built on the mechanism “case  pattern  strategy”. Two methodological components, Proactive Redesign Decomposition and Redesign Condition Analysis, are introduced in the article.


Proactive approach
The pattern-based reasoning mechanism discussed in previous blog is treated as a knowledge base to support the development of the rapid redesign methodology. Particularly, redesign cases and scenarios support the formation of pattern solutions for any redesign problems represented by DDM. Then, redesign strategies provide a finite range of tactics that help to systematically develop a detailed redesign roadmap for any redesign scenario. There are two components for the proactive redesign approach: Proactive Redesign Decomposition and Redesign Condition Analysis.

Proactive redesign decomposition
The development of Proactive Redesign Decomposition is based on the two-phase decomposition method. The first phase of this method, termed dependency analysis, is applied such that the scattered ‘‘1’’ elements in the original DDM get close to one another to form clusters. For most of complex problems in practice, the banded diagonal matrix will be obtained, which indicates the existence of interactions between the formed clusters. After obtaining the banded diagonal matrix, the second phase, termed matrix partitioning, is invoked. In this phase, three decomposition criteria are required in order to generate decomposition solutions: number of blocks, size limit of each block, and size limit of interaction parts.
The pattern complexity metric is a relative measure that estimates the potential design (computing) effort associated with a model-specific pattern. The block size balance is measured via the SD of the block sizes. Both of these values are used to analyze and refine the generated set of decomposition solutions, thus finally forming the model-specific pattern library


Redesign condition analysis
After obtaining the model-specific pattern library, the proactive redesign approach is ready to receive redesign requests, which activate the Redesign Condition Analysis. In this analysis, the incoming redesign requests are interpreted and translated into the corresponding target entities in the DDM. Then, the target entities are labeled in the model-specific patterns to form pattern solutions. Also, it is required to identify the redesign cases in order to select the proper root patterns from the model-specific pattern library. As a result, the applicable pattern solutions are identified to form the pattern selection space. At this point, the Redesign Planning Analysis can be applied to finally generate the redesign roadmap for the guidance of the redesign solution process.


Conclusion
The proactive redesign approach in this paper utilizes the two-phase decomposition method to generate decomposed structures of a given model to approximate its potential pattern solutions. Thus, as long as the existing model is kept the same, no further decomposition is required for new redesign requests. This proactive technique is applicable to existing design models that are subject to frequent yet minor design changes.
In short, the proactive redesign can generate a library that contains the best combination of process patterns that allowing certain changes. If we find some process sequence needed to be change, other patterns can be used to replace the existing method instantly since all the calculation is done preliminary. Compare with the previous approach, the proactive redesign can actually pay some efforts before the redesign is conducted. Also, once the computation is done, it can be reused in the future subject to no rapid change to the process dependency and sequence. 

Week 12 - Redesign Principles and Tactics (2)

Source / Reference:
1)"Model-based Rapid Redesign Using Decomposition Patterns" by Chen, Li ; Macwan, Ashish ; Li, Simon
J. Mech. Des.  -- March 2007 --  Volume 129,  Issue 3, 283
http://scitation.aip.org.ezproxy.lb.polyu.edu.hk/getabs/servlet/GetabsServlet?prog=normal&id=JMDEDB000129000003000283000001&idtype=cvips&gifs=yes




Subject:
Other model of process redesign: Model-based Rapid Redesign


Motivation:

We have been taught about the Five Phases BPR Methodologies and in the phase three - process redesign, there are many redesign principles and tactics, such as Streamline, Lose Wait, Orchestrate, Mass-customize, Synchronize, Digitize and Propagate, etc. These redesign tactics and principles mainly depend on human involvement. Is there any other ways to help redesigning process in a systematic approach which can be done by system? I have found an article that may explore the possibility of process redesign that can be assisted by some mathematical approaches. The article is “Model-based Rapid Redesign Using Decomposition Patterns”, although the title seems like talking about redesign, it is not fully related to redesign a process. However, the idea and methodology discussed may be useful for redesign a business process.


Introduction to Model-based Rapid Redesign Using Decomposition Patterns
The article presents a pattern-based decomposition methodology for rapid redesign to support design customization in agile manufacturing of evolutionary products. The methodology has three functional phases. The first phase, called design dependency analysis, systematizes and reorganizes the intrinsic coupling structure of a given existing design model that is represented using the design dependency matrix. The second phase, called redesign partitioning analysis, generates alternative redesign pattern solutions to form a solution selection space through a three-stage procedure. The third phase, called pattern selection analysis, finds an optimal redesign pattern solution that entails the least potential redesign effort. Each pattern solution identifies and delimits the portions of the design model that need to be recomputed, thus expediting the redesign solution process. In such a way, one can treat the re-computation of the entire model, which is a conventional and computation-expensive solution approach, only as the last resort to solve the redesign problem given.


1st phase: design dependency analysis
A general redesign problem is formulated as a constraint-based computational model that is composed of parameters and constraint functions. The parameters describe the physical constituents and/or behavioral properties of concern for a design. And the constraint functions define the design correlations and mappings between the parameters. In this context, the design dependency matrix (DDM), a mathematical incidence matrix, can be used to capture and convey the dependency information inherent in the design model. The DDM-assisted decomposition can be applied as an effective means for simplifying the design problems that are intractable in size and complexity.


2nd phase: redesign partitioning analysis
The goal of partitioning is to convert a diagonal matrix into possible pattern solutions, or rather, to identify which redesign decomposition patterns from the library and their redesign pattern solutions correspond to the diagonal matrix. Upon the concept of the partition point, the redesign partitioning analysis is developed to address the placement of partition points in order to generate all the applicable redesign pattern solutions from a diagonal matrix.


3rd phase: pattern selection analysis
To provide a means to evaluate alternative pattern solutions to find the optimal one, two matrix pattern metrics are derived to quantify the redesign effort entailed by any given redesign pattern solution: intensity and interdependency. The intensity metric is used to estimate the scale of redesign potentially involved in improving the deficient performance levels. Also, the interdependency metric is used to estimate the redesign propagation potentially induced due to coupling.

Conclusion
This model uses mathematical methodology to analysis the dependency among process and decomposes the process. Through this analysis, the partitioned process can be analyzed and redesigned to obtain the optimal process pattern.
We can apply this model in redesigning a business process. First we have to define the dependency of activities with a business process. Then we can build a design dependency matrix and follow the three phase methodology above. Finally, we can get the best possible redesigned process. However, the mentioned methodology has a greater improvement on complex process. If the process is rather simple, the model may not be very useful for redesigning since the dependency and sequence are non-changeable. 
If we can apply this model agilely with the redesign principles and tactics, a better process can then be redesigned.