Developing performance measurement system for Internet of Things and smart factory environment

Hwang, Gang Uk; Lee, Jeongcheol; Park, Jin-Woo; Chang, Tai‐Woo

doi:10.1080/00207543.2016.1245883

Cited by 155 publications

(82 citation statements)

References 20 publications

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“…These relationships are often undermined in organizations, leading to analytical complexity (Suwingnjo et al 2000) Analytical complexity is often associated with a lack of understanding regarding cause and effect relationships between measures, data presentation, sophisticated charts and graphs, and visual screens. In another study by Hwang et al (2017), the workability of the internet of things (IoT) for capturing real-time data was investigated: technical controls such as simulation results, planned and actual production data, timestamp data acquired by IoT were identified leading to analytical complexity. These analytical approaches restrict subjectivity, ambiguity and conflict between measures (Santos et al 2002).…”

Section: S Okwir Et Almentioning

confidence: 99%

Performance Measurement and Management Systems: A Perspective from Complexity Theory

Okwir

Nudurupati

Ginieis

et al. 2018

Int J Management Reviews

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Complexity negatively impacts the process of continually improving performance management systems (PMSs). The extant PMS literature considers complexity to be a result of the external environment rather than a user response to that environment. However, this paper argues that organizations generally face internal complexity when adopting PMSs. Introducing PMSs into an organization can have varied effects in those organizations based on the complexity of an organization's associated members and its interactions. This study aims to understand the emergence of complexities while implementing and using PMSs in organizations. From the complexity theory perspective, four system properties (ontological, teleological, genetic and functional) are used to understand complexity in PMSs. The paper builds on a systematic literature review consisting of 76 papers and analyses them in the light of exploring sources of complexity when implementing and using PMSs. From the outset, complexity is understood to be a result of the conflict between existing organizational practices and mechanisms and the organizational controls associated with PMSs. The key findings abstracted six sources of complexity in this study: role, task and procedural types of complexity associated with the social dimension, and methodological, analytical and technological types of complexity associated with the technical dimension. The study findings contribute to the current discussion regarding why PMSs typically lag and are not responsive and resilient in emerging contexts. While understanding and exploring all organizational controls that moderate a PMS is useful, organizations should construct the necessary capabilities, depending on their context and adapt to the changes associated with PMSs.

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Section: S Okwir Et Almentioning

confidence: 99%

Performance Measurement and Management Systems: A Perspective from Complexity Theory

Okwir

Nudurupati

Ginieis

et al. 2018

Int J Management Reviews

View full text Add to dashboard Cite

show abstract

“…Second, LCA, life cycle costing (LCC), and life cycle sustainability analysis (LCSA) methods can be integrated to ensure adequate sustainability in terms of economic, environmental, and social benefits (da Luz, de Francisco, Piekarski, & Salvador, ; Peruzzini, Gregori, Luzi, Mengarelli, & Germani, ). Further, a more sophisticated data collection system is worthy of development, for the objective of conducting a throughout analysis on all the influential factors (Hwang, Lee, Park, & Chang, ), including analyzing uncertainties.…”

Section: Discussionmentioning

confidence: 99%

Can smart factories bring environmental benefits to their products?: A case study of household refrigerators

Zhang

Guo

2019

J of Industrial Ecology

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Smart factories have been widely adopted as a new manufacturing paradigm, in which the state‐of‐the‐art technologies are introduced to improve relevant processes. Yet, whether smart factories affect the environmental performance remains unknown. In this article, we examine the environmental performance of a smart refrigerator factory by comparing the environmental impacts of its product to a similar model that is produced in a traditional fashion. This article quantifies and verifies the theoretically predicted impacts of this smart factory on the individual processes. Though the overall differences in the two models are quite minor, we find that this smart factory can notably reduce the values of most impact categories associated with the parts and refrigerator production; the reduction in the value of climate change is 33%. Owing to higher material efficiency—raw material savings in this smart factory contributes to the greatest reductions in most categorized impacts—the contribution to the reduction of climate change is 39%. Yet, all categorized impacts of procurement and delivery are increased due to product personalization and direct delivery. The results of sensitivity analysis show that promoting product modularity, adopting clean energy such as wind power can further improve the environmental performance of the selected refrigerator. The introduction of auxiliary equipment and systems slightly increases the value of each category; yet their impacts are negligible compared to their benefits as facilitating production efficiency. Based on the quantitative results, recommendations are given to improve the environmental performance of smart factory, including optimizing current strategies and promoting horizontal and end‐to‐end integration.

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“…From here on, the methodology that has these initial weightings will be called the simple methodology. At first, we selected assessment items from existing literatures [8,10,11,18], identifying the list of criteria and sub-criteria with consultants and scholars and specifying the detailed core activities of each criterion as shown in Table 1. Based on the field survey with five consultants who had experience with manufacturing innovation projects, we narrowed down the list to 4 criteria and 10 sub-criteria according to the conceptual framework, and grouped 46 assessment items according to the criteria.…”

Section: Identifying the Assessment Criteria Based On Literature Reviewmentioning

confidence: 99%

“…Performance measures can be obtained through a combination of various operation measurements, i.e., key performance indicators (KPIs). ISO-22400 defines the application of KPIs, which are presented with their formulas and corresponding elements [11].…”

Section: Assessment and Certification Systems Of Factoriesmentioning

confidence: 99%

A Smartness Assessment Framework for Smart Factories Using Analytic Network Process

et al. 2017

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Abstract:The so-called smart factory is a novel paradigm that is rapidly gaining ground in scenarios for factories of the future. Many manufacturing companies try to raise the level of smartness by considering a number of aspects related to the smart factory. However, there is a lack of field-oriented systematic research to help them fit the interest of industry for promoting interest and diffusion of smart factory. Moreover, it is still difficult to assess whether the vision of the future factory that incorporates information and communication technologies is implemented. Therefore, in this study, we propose a smartness assessment framework for smart factories which is based on the concept of operation management so as to be easy to make manufacturing companies to understand and apply. The framework is composed of evaluation criteria and sets the weightings of the criteria using analytic network processes. From a case study based on 20 small and medium-sized manufacturing enterprises, the effectiveness of the proposed framework has been verified.

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Developing performance measurement system for Internet of Things and smart factory environment

Cited by 155 publications

References 20 publications

Performance Measurement and Management Systems: A Perspective from Complexity Theory

Performance Measurement and Management Systems: A Perspective from Complexity Theory

Can smart factories bring environmental benefits to their products?: A case study of household refrigerators

A Smartness Assessment Framework for Smart Factories Using Analytic Network Process

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