A clustering approach for modularizing service-oriented systems

Ezzat, Omar; Medini, Khaled; Boucher, Xavier; Delorme, Xavier

doi:10.1007/s10845-020-01668-w

Cited by 9 publications

(4 citation statements)

References 30 publications

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“…It is a fundamental element for the optimization of the supply chain, which allows the quick respond to the demands (Biswas, 2017 ). (Ezzat et al, 2020 ) consider modularity as an effective method to better manage product and service variation. Comparing with RMS, modularity was measured through granularity and number of interfaces.…”

Section: Proposed Approachmentioning

confidence: 99%

New metrics for measuring supply chain reconfigurability

2021

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The COVID 19 pandemic, fluctuating demand, market uncertainty and the emergence of new technologies explain the need for a more flexible and agile supply chain. In fact, several important factors should be taken into account in the process of building an adaptive and reconfigurable supply chain. Reconfigurability is used to measure quantitatively the capability of supply chain to change easily their structure and functions. The aim of this work is to evaluate the level of reconfigurability of a supply chain. Quantitative measures of six indicators that characterize reconfigurability are presented in this paper. Then, an index of reconfigurability in supply chain is developed based on The Multi-Attribute Utility Theory in order to choose the most reconfigurable configuration. An illustrative example is also given. From the discussion, it is deduced that the characteristics of the reconfigurable supply chain impacts positively on the degree of reconfigurability.

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Section: Proposed Approachmentioning

confidence: 99%

New metrics for measuring supply chain reconfigurability

2021

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“…Both groups share the fact that they form modules mostly on the basis of functional dependencies. For this purpose, often based on the Design Structure Matrix (DSM) (Eppinger and Browning, 2012), dependencies between the components are put into a matrix and then corresponding clusters of modules are formed (Sakao et al, 2017;Ezzat et al, 2019Ezzat et al, , 2020. The module composition can be supported by various algorithms (Sun et al, 2017;Song and Sakao, 2017;Chen et al, 2020).…”

Section: Background and Research Needmentioning

confidence: 99%

Life Phases Modularisation of Product-Service Systems

Rennpferdt

Krause

2021

Proc. Des. Soc.

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Product Service Systems (PSS) are increasingly important for companies. They enable a multitude of advantages, including the ability to offer customers even more individual customised solutions. However, PSS can also cause negative effects for companies. For example, PSS increase the complexity within companies. In order to cope with this complexity, the modularisation of PSS is frequently suggested in literature. However, existing approaches for modularisation only consider functional reasons for module composition and neglect the product-strategic aspects. This paper introduces a new approach for the modularisation of PSS, which combines functional and product-strategic aspects into one approach. To achieve this, a separate modular structure is developed for each life phase. Following this, these are harmonised across all life phases. This enables the advantages of the modular PSS structure to be used in all life phases. A PSS family of laser processing machines is used to illustrate the new developed approach.

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“…electrical, design and mechanical engineers for design and manufacturing, technicians for cleaning, highly qualified operators for maintenance activities (maintenance engineers, qualified technicians...), qualified personnel for after-sales services and training. Human resources as a grouping criterion can heavily influence the generation of different modularity scenarios mixing product and service in consistent modules [13]. Table 2 briefly illustrates the human resource type related to each element of product and service.…”

Section: Case Studymentioning

confidence: 99%

“…The two scenarios result from different clustering methods and parameters but they share the same input elements : scenario 1 is based on modules Measuring Complexity for Collaborative Business Processes Management 243 containing no more than two components each (product and/or service): {E1, E12}, {E9}, {E6}, {E15}, {E16}, {E18}, {E20,E21}, {E5,E4}, {E17}, {E19}, scenario 2 relies on clusters made from several products and services: {E1,E12,E6,E9}, {E15,E16,E18}, {E20,E21}, {E4,E5}, {E17, E19}. For deeper discussion on how to build and generate different product and service modularity scenarios, the reader can report to the full study in [13].…”

Section: Case Studymentioning

confidence: 99%

Measuring Complexity for Collaborative Business Processes Management

Marzouk

Ezzat

Medini

et al. 2021

IFIP Advances in Information and Communication Technology

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Organizations are increasingly working on business processes improvement to meet stakeholders' requirement. Process engineering and improvement projects are challenged by identifying proper metrics to guide improvement efforts and mitigate process complexity. This latter is intuitively related to factors such as usability, modularity, reliability and maintainability. A process that is too complex is more likely to fail and produce costly quality problems. In a context of collaborative decision-making, complexity management must consider the expectations of several stakeholders, and the definition/use of suitable metrics is the starting point. The current paper identifies and uses a set of metrics to enable the evaluation of process models. The proposed metric system is used within a case study highlighting the key role of modularity in mitigating process complexity. More generally, the results show how using the metric system can support complexity mitigation and therefore performance improvement in (re)engineered processes.

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A clustering approach for modularizing service-oriented systems

Cited by 9 publications

References 30 publications

New metrics for measuring supply chain reconfigurability

New metrics for measuring supply chain reconfigurability

Life Phases Modularisation of Product-Service Systems

Measuring Complexity for Collaborative Business Processes Management

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