Zero Defect Manufacturing in an Industry 4.0 Context: A Case Study of Requirements for Change and Desired Effects

Lindström, John; Kyösti, Petter; Lejon, Erik; Birk, Wolfgang; Andersson, Åke E.; Borg, Mikael; Juntti, Mikael; Suupf, Anna-Maria; Germain, Maria; Hermanson, Anders; Gunnarson, Bengt

doi:10.2139/ssrn.3717709

Cited by 7 publications

(6 citation statements)

References 13 publications

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“…The initial model for ZDM outlined in Section 4 is intended to be generic and adaptable primarily for manufacturing but also for process industry companies. As stated in the introduction, our view on ZDM is based on our previous research [3,7,8], and combines and integrates seven areas analyzed towards the initial model:…”

Section: Discussionmentioning

confidence: 99%

“…The main challenges associated with ZDM have been to integrate large amounts of information from many sources, the need to develop advanced technology and methods, the modeling of ZDM, and timely (on-line or in real-time) computing [2]. These issues have also been confirmed by a recent ZDM research study with six participating manufacturing and process industry companies [3]. There, the needs and desired effects from applying ZDM are also elaborated on.…”

Section: Introductionmentioning

confidence: 92%

“…Today, the ZDM-drivers are, for most manufacturing and process industry companies, to become more competitive, profitable, sustainable and intelligent with related effects, such as: lower costs, lower energy consumption (per output), lower level of wasted materials and scrapped output, faster production processes, better overview of the production process, improved planning ability, production systems robustness and resilience, higher level of availability, and improved level of output quality [2,3,8].…”

Section: Introductionmentioning

confidence: 99%

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An Initial Model for Zero Defect Manufacturing

Lindström¹,

Kyösti

Birk

et al. 2020

Applied Sciences

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This paper investigates an initial model for Zero Defect Manufacturing (ZDM) using a cost function where the operation and condition of a production process are reflected, and the quality of the output/product and the production process (as well as safety aspects) can be considered. The outset of the study is based on empirical data collected from five manufacturing companies, and proposes an initial model for ZDM with an Industry 4.0 perspective. The initial ZDM model has a generic setup for a real-life system and its replication as a digital twin using system models based on a representation of a generic production process with its connected control system, and potential interconnections between unit processes. It is based on concepts from system theory of dynamic systems and principles from condition monitoring and fault detection. In that way the model is deemed as highly generalizable for manufacturing and process industry companies as well as for some critical infrastructures with production and distribution systems. The proposed model with its cost function setup is analyzed and discussed in the context of ZDM. It is concluded that production processes in the manufacturing and process industry can be made more intelligent and interoperable using this approach. Improved sustainability, competitiveness, efficiency and profitability of companies are foreseen welcomed secondary effects. Finally, the proposed ZDM model further develops the ZDM by adding to it a systematic approach based on a solid mathematical foundation.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

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An Initial Model for Zero Defect Manufacturing

Lindström¹,

Kyösti

Birk

et al. 2020

Applied Sciences

Self Cite

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“…Traditional QI methods were designed using the technologies available at the time, without the knowledge of recent technological advances under the framework of Industry 4.0 (Psarommatis et al, 2020b). Methods such as artificial intelligence, machine learning or semantic modelling present new ways for manufacturers to achieve targets that would have been impossible in the past (Lindström et al, 2020).…”

Section: The Promise Of Zero-defect Manufacturingmentioning

confidence: 99%

A semantic systems engineering framework for zero-defect engineering and operations in the continuous process industries

Cameron

Waaler

Fjøsna³

et al. 2022

Front. Manuf. Technol.

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The on-going twin transition demands that the continuous process industry builds and operates their facilities in a more sustainable way. This change affects the entire supply-chain. The market demands new ways of engineering, procuring and constructing plants that assure quality at each step of the process. Petroleum and petrochemical producers must reduce their waste and environmental footprint and find ways of migrating to sustainable production. There is zero tolerance for waste, emissions or process malfunctions. Engineering contractors need to transfer their skills to new processes and produce series, non-custom facilities for new applications like offshore wind energy, modular production and industrial symbiosis. This is leading to a convergence in methods with discrete manufacturing, especially the automotive industries. In this climate, this sector can benefit from applying Zero-defect Manufacturing (ZDM) to both engineering design and operations. This work defines a framework for implementing ZDM in the process industry supply chain. The framework brings together modelling techniques and models from the following disciplines: system engineering, computer-aided process engineering, automation (especially Industry 4.0) and semantic technologies. These contributions are synthesised into an information fabric that allows engineering firms to work in new ways. Operators and contractors can use the fabric to move from document-driven engineering to data-based processes. The fabric captures requirements and intent in design so that facilities can be delivered and started-up and operated with zero defects in the design and construction. The information is also a vital support for safe and efficient operations and maintenance. We call this zero-defect O&M. The framework combines a systems engineering break-down of facilities, based on ISO/IEC81346, with implementation in SysML, with semantic interoperability frameworks from the process industries (ISO15926). We build upon and synthesise the results of recent standardization initiatives from the industry, notably CFIHOS, DEXPI and READI. We draw on results from process systems engineering, the OntoCAPE ontology and the CAPE-OPEN standards. The framework is illustrated by application to a non-proprietary process system, namely the Tennessee-Eastman process. This example is used to show the modelling approach and indicate how the fabric supports zero-defect practices.

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“…In order to achieve ZDM, it is absolutely necessary to detect abnormalities in the manufacturing system in real time, to predict and prevent various factors that can affect quality in advance, and to take quick action and repair for the parts where the problem occurs. According to Lindström et al (2019Lindström et al ( , 2020b, ZDM tries to combine and integrate the following seven activities: 1) Monitoring of process parameters; 2) Collaborative manufacturing; 3) Continuous quality control; 4) On-line predictive maintenance; 5) Data storage, analytics and visualization; 6) Re-configuration and re-organization of production; and (7) Re-scheduling of production. ZDM has several approaches such as product-oriented, process-oriented, and people-oriented ZDM, depending on where we look at the target for reducing defects.…”

Section: Zero Defect Manufacturingmentioning

confidence: 99%

A Review on the Advanced Maintenance Approach for Achieving the Zero-Defect Manufacturing System

Jun

2022

Front. Manuf. Technol.

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Recently, a revolutionary change is taking place in manufacturing and production systems thanks to the development of various advanced technologies such as IIoT (Industrial Internet of Things), CPPS (Cyber-Physical Production System), digital twins, big data analytics, AI (Artificial Intelligence), and so on. One of the change is that manufacturing and production systems are now trying to transform into the ZDM (Zero-Defect Manufacturing) system. For a manufacturing company, quality takes precedence over any other competitive factors, so the implementation of a ZDM system is very important. For the implementation of ZDM, many fundamental technologies are required. Among them, the advanced maintenance approach for the facilities/equipment of the manufacturing and production system is much more important because it could support the zero-defect and high-efficiency operation of manufacturing and production systems. The advanced maintenance approach, which is often called by various terms such as predictive maintenance, condition-based maintenance plus (CBM+), and PHM (Prognostics and Health Management), requires various interdisciplinary knowledge and systematic integration. In this study, we will review previous works mainly focusing on advanced maintenance subject among ZDM research works, and briefly discuss the challenging issues for applying PHM technologies to the ZDM.

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Zero Defect Manufacturing in an Industry 4.0 Context: A Case Study of Requirements for Change and Desired Effects

Cited by 7 publications

References 13 publications

An Initial Model for Zero Defect Manufacturing

An Initial Model for Zero Defect Manufacturing

A semantic systems engineering framework for zero-defect engineering and operations in the continuous process industries

A Review on the Advanced Maintenance Approach for Achieving the Zero-Defect Manufacturing System

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