Cost-Based Decision Support System: A Dynamic Cost Estimation of Key Performance Indicators in Manufacturing

Psarommatis, Foivos; Danishvar, Morad; Mousavi, Amir; Kiritsis, Dimitris

doi:10.1109/tem.2021.3133619

Cited by 9 publications

(3 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The outcome of this methodology is a tool that can assist manufacturers in the decision-making process when selecting between product or process ZDM approaches. This assistance consists of comparing the different solutions for ZDM implementation and, based on the suggested cost function, selecting the most efficient approach [64]. In Section 4, the proposed product-and process-oriented models are analyzed in detail, and the effect of each model parameter is quantified using design of experiments (DoE) based on the Taguchi approach [65].…”

Section: Modelling Procedures and Analysis Methodsmentioning

confidence: 99%

A Systematic Analysis for Mapping Product-Oriented and Process-Oriented Zero-Defect Manufacturing (ZDM) in the Industry 4.0 Era

Psarommatis

May

2023

Sustainability

Self Cite

View full text Add to dashboard Cite

Quality is a key aspect in the era of Industry 4.0. Zero-defect manufacturing (ZDM) as the latest quality assurance approach. It can be implemented in two different approaches: the product-oriented and the process-oriented ZDM. It is important to know how and when to consider adopting one approach over the other. To achieve that there is the need for analyzing the differences of the two ZDM approaches. However, the current literature lacks a detailed analysis and comparison of these two approaches to ZDM implementation. Earlier studies on the topic have adopted one of these approaches over the other without evaluating how it fits with specific cases. The literature of the last decade indicates a movement towards product-oriented approaches, but it has not shown proof why product oriented was used over process oriented. Guided by these gaps, this research work creates a model for quantifying the effects of the implementation of both the product-oriented and process-oriented ZDM approaches. The proposed model considers all the critical parameters that affect the problem and serves as an assisting tool to engineers during the design or re-configure manufacturing systems, for choosing the most efficient ZDM approach for their specific cases. The robustness of the model was analyzed using the design of experiments method. The results from both the designed experiments and an industrial use case illustrate that in most cases, product-oriented ZDM performs better than the process-oriented approach. Nevertheless, in our analysis, we also highlight strong interactions between some factors that make the selection between product-oriented and process-oriented ZDM difficult and complex.

show abstract

Section: Modelling Procedures and Analysis Methodsmentioning

confidence: 99%

A Systematic Analysis for Mapping Product-Oriented and Process-Oriented Zero-Defect Manufacturing (ZDM) in the Industry 4.0 Era

Psarommatis

May

2023

Sustainability

Self Cite

View full text Add to dashboard Cite

show abstract

“…Microelectronics and hard metal composite manufacturers were given the task of controlling and optimizing resource utilization, production efficiency, product-process quality, environmental impact, and inventory. Thus, Psarommatis et al (2022) aim to make decision-making easier by converting data from operations management into dynamic financial cost models. The process of converting engineering data from the physical level and operations management level into financial metrics establishes a common language among engineers, managers, and financial departments of a company, all of whom have their own priorities but share the same goal of increasing profitability.…”

Section: Figurementioning

confidence: 99%

Advances in Adaptive Scheduling in Industry 4.0

Mourtzis

2022

Front. Manuf. Technol.

View full text Add to dashboard Cite

The shift of traditional mass-producing industries towards mass customisation practices is nowadays evident. However, if not implemented properly, mass customisation can lead to disturbances in material flow and severe reduction in productivity. Moreover, manufacturing enterprises often face the challenge of manufacturing highly customized products in small lot sizes. One solution to adapt to the ever-changing demands, which increases resource flexibility, lies in the digitization of the manufacturing systems. Furthermore, the distributed manufacturing environment and the ever-increasing product variety and complexity result in reduced time-to market, ubiquitous data access and sharing and adaptability and responsiveness to changes. These requirements can be achieved through smart manufacturing tools and especially Wireless Sensor Networks (WSN). Thus, the aim of this position paper is to summarize the design and development of solutions based on cutting-edge technologies such as Cloud Computing, Artificial Intelligence (AI), Internet of Things (IoT), Simulation, 5G, and so on. Concretely, the first part discusses the development of a Cloud-based production planning and control system for discrete manufacturing environments. The proposed approach takes into consideration capacity constraints, lot sizing and priority control in a “bucket-less” manufacturing environment. Then, an open and interoperable Internet of Things platform is discussed, which is enhanced by innovative tools and methods that transform them into Cyber-Physical Systems (CPS), supporting smart customized shopping, through gathering customers’ requirements, adaptive production, and logistics of vending machines replenishment and Internet of Things and Wireless Sensor Networks for Smart Manufacturing. To that end, all the proposed methodologies are validated using data derived from Computer Numerical Control (CNC) machine building industry, from European Metal-cutting and mold-making SMEs, from white goods industry and SMEs that produces solar panels.

show abstract

“…Dashboards provide a synthesised, aggregated and interactive way of visualising information critical to business decision-makers and can proactively alert them to existing problems. At the strategic level, through business intelligence systems, it is possible to define the main goals (the organisation's strategic key performance indicators) and objectives and to monitor them [5,6].…”

Section: Introductionmentioning

confidence: 99%

Developing Integrated Performance Dashboards Visualisations Using Power BI as a Platform

Gonçalves,

Campante

2023

Information

View full text Add to dashboard Cite

The rapid advance of business technologies in recent years has made knowledge an essential and strategic asset that determines the success or failure of an organisation. Access to the right information in real time and with high selectivity can be a competitive advantage in the business environment. Business intelligence systems help corporate executives, business managers, and other operational workers make better and more informed business decisions. This study aimed to assess the impact of using business intelligence tools on the decision-making process in organisations, specifically in sales marketing. The methodology applied to realise the study’s objective was the Vercellis methodology. A set of data available on the sales marketing website SuperDataScience was used to implement a set of pressing KPIs for the business decision-making process in the area. Using these data, a complete business intelligence system solution was implemented. A data warehouse was created using the ETL (extract–transform–load) process, and the data were then explored using a set of dynamics dashboards with a view of the business metrics. The results showed the use of business intelligence systems that allow the integration and transformation of data from various sources stored in data warehouses, where it is possible to implement KPIs and carry out quick, concise, easy-to-interpret graphical analyses. This paper contributes to a better understanding of the importance of data-integrated dashboard visualisation for the decision-making process.

show abstract

Cost-Based Decision Support System: A Dynamic Cost Estimation of Key Performance Indicators in Manufacturing

Cited by 9 publications

References 59 publications

A Systematic Analysis for Mapping Product-Oriented and Process-Oriented Zero-Defect Manufacturing (ZDM) in the Industry 4.0 Era

A Systematic Analysis for Mapping Product-Oriented and Process-Oriented Zero-Defect Manufacturing (ZDM) in the Industry 4.0 Era

Advances in Adaptive Scheduling in Industry 4.0

Developing Integrated Performance Dashboards Visualisations Using Power BI as a Platform

Contact Info

Product

Resources

About