Extending the information-theoretic measures of the dynamic complexity of manufacturing systems

Smart, Janet; Calinescu, Anisoara; Huatuco, Luisa Huaccho

doi:10.1080/00207543.2011.638677

Cited by 32 publications

(19 citation statements)

References 26 publications

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“…In related literature on manufacturing, complexity is usually classified into two categories: structural (static) and operational (dynamic) (see Frizelle and Woodcock 1995;Deshmukh, Talavage, and Barash 1998;Sivadasan et al 2002). According to Smart, Calinescu, and Huaccho Huatuco (2011), 'structural (also known as static) complexity is the amount of information needed to describe the state of the manufacturing facility as derived from the production schedule, i.e. according to the structure or plan of the manufacturing facility.…”

Section: Entropy Approaches Of Type Imentioning

confidence: 99%

“…Since Shannon's information entropy (Shannon 1948) enables a detailed analysis of the structure of occurring deviations from target values, several authors propose entropy-based measures for various problems in manufacturing or supply chain management (see, among others, Yao 1985;Ronen and Karp 1994;Frizelle and Woodcock 1995;Deshmukh, Talavage, and Barash 1998;Sivadasan et al 2002;Sivadasan et al 2006;Martínez-Olvera 2008;Smart, Calinescu, and Huaccho Huatuco 2011;Wu et al 2012). Due to an information theoretic definition of complexity, these approaches apply entropy values.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

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A new two-dimensional performance measure in purchase order sizing

Bock

Isik

2015

International Journal of Production Research

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Lack of knowledge about demand responses or about behavioural aspects of decision-making within procurement processes is a significant cost driver in modern supply chains. Very often, this lack of knowledge leads to a substantial increase in inventories and may endanger negotiated service levels. For instance, various studies reveal that decision-makers tend to anchor orders close to the average past demand although the target order size is significantly higher or lower. In order to improve this situation, feedback has to be systematically provided to the decision-makers. In combination with modern big data analytics and reporting instruments that enable exhaustive monitoring, effective indicators have to be applied in order to directly detect processes with significant potential for improvement. Hence, this paper proposes a new approach for measuring the intricacy in purchase order sizing that addresses self-awareness skills of decision-makers. By simultaneously analysing the amount and structure of occurring costs, processes with a significant and simple structured error pattern are identified. In order to identify these processes more reliably, a new approach that supplements former information-theoretic entropy measures by an additional cost value is proposed. By analysing costs and the structure of deviations from target values in a two-dimensional measure, a more comprehensive understanding of the considered order sizing process is pursued. In order to illustrate the application of the new approach and show limitations of one-dimensional measures, different scenarios that exemplify the new approach are presented.

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Section: Entropy Approaches Of Type Imentioning

confidence: 99%

Section: Introduction and Literature Reviewmentioning

confidence: 99%

A new two-dimensional performance measure in purchase order sizing

Bock

Isik

2015

International Journal of Production Research

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“…Duan et al [11] aimed at the deficiency of the present structural complexity modeling problem, put forward a structural complexity modeling and evaluation method of non-serial manufacturing systems based on considering the influences of the buffers' states on the overall manufacturing systems. Smart et al [12] studied the dynamic complexity of manufacturing system based on the improved information entropy, analyzed the production process and queue status, and expounded the relationship between the system complexity and operation situation. Liu et al [13] studied in the generating mechanism of polymorphism and brittle excitation mechanism, proposed the brittle risk of motivators, coupling and brittle degrees of quantitative method using the state space model.…”

Section: Introductionmentioning

confidence: 99%

Decision-making method of reconfigurable manufacturing system's reconfiguration timing based on catastrophe theory

Huang

Wang

Yan

2015

2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

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For the problem how to make the decision of RMS's reconfiguration timing, a decision-making method based on information entropy and cusp catastrophe theory is proposed. The information entropy was used to characterize the complexity of RMS, including the factors of machine states, part states and so on. The RMS passive and positive information entropies were used as control variables of cusp catastrophe. According to the cusp catastrophe mutation determination condition, the RMS mutation point was decided, which was the RMS's reconfiguration time. A case study validated the effectiveness and practicability of the method proposed, which guided the launch of RMS reconfiguration in time and improve the response ability of RMS.

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“…Several researchers have studied the subject of knowledge and its valuation (Bernard and Xu 2009;Xu and Bernard 2010;Xu et al 2014;Magee et al 2016). Knowledge representation and knowledge creation in manufacturing systems and in product development in general, is presented in (Henriksen and Rolstadås 2010;Wu et al 2014 Lu and Suh 2009;ElMaraghy et al 2012;Chryssolouris et al 2013;Smart, Calinescu, and Huaccho Huatuco 2013) used the information theory, complexity measures and uncertainty in an attempt to quantify the information exchange and thus, the knowledge content, throughout the production of a certain product. A general definition of knowledge is: • Information, understanding or skill that you acquire from experience and/or education • awareness of something…”

Section: Introductionmentioning

confidence: 99%

Dematerialisation of products and manufacturing-generated knowledge content: relationship through paradigms

Petrides

Papacharalampopoulos

Stavropoulos

et al. 2017

International Journal of Production Research

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Dematerialisation refers to the decline, over time, of material usage in industrial products. The subject of this paper is to identify the relationship between the material and knowledge content of several products. The issue is whether the knowledge content, through time, will be affecting the products, in terms of dematerialisation. Specifically, a study has been conducted on widely used products in order to determine the way they have changed through their life-timeline. Two different indicators have been introduced for the quantification of the trend, in terms of material and knowledge content.

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Extending the information-theoretic measures of the dynamic complexity of manufacturing systems

Cited by 32 publications

References 26 publications

A new two-dimensional performance measure in purchase order sizing

A new two-dimensional performance measure in purchase order sizing

Decision-making method of reconfigurable manufacturing system's reconfiguration timing based on catastrophe theory

Dematerialisation of products and manufacturing-generated knowledge content: relationship through paradigms

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