Factory Floor Research Articles

Smooth and Resilient Human–Machine Teamwork as an Industry 5.0 Design Challenge

Smart machine companions such as artificial intelligence (AI) assistants and collaborative robots are rapidly populating the factory floor. Future factory floor workers will work in teams that include both human co-workers and smart machine actors. The visions of Industry 5.0 describe sustainable, resilient, and human-centered future factories that will require smart and resilient capabilities both from next-generation manufacturing systems and human operators. What kinds of approaches can help design these kinds of resilient human–machine teams and collaborations within them? In this paper, we analyze this design challenge, and we propose basing the design on the joint cognitive systems approach. The established joint cognitive systems approach can be complemented with approaches that support human centricity in the early phases of design, as well as in the development of continuously co-evolving human–machine teams. We propose approaches to observing and analyzing the collaboration in human–machine teams, developing the concept of operations with relevant stakeholders, and including ethical aspects in the design and development. We base our work on the joint cognitive systems approach and propose complementary approaches and methods, namely: actor–network theory, the concept of operations and ethically aware design. We identify their possibilities and challenges in designing and developing smooth human–machine teams for Industry 5.0 manufacturing systems.

Reverberation Chamber Metrology for Wireless Internet of Things Devices: Flexibility in Form Factor, Rigor in Test

Internet of things (IoT) devices are proliferating in our connected world, with the number of devices expected to exceed 14 billion in 2023 <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> . Wireless IoT applications are increasing day by day, ranging from cellular-enabled parking meters that can validate your credit card in real time, to trash compactors that inform the garbage company when they are full, to wireless local-area-network–enabled industrial programmable logic controllers (PLCs) that control robots on the factory floor with micron precision. The physical size and shape or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">form factor</i> of these devices can range from millimeters to meters on a side, and latency requirements can range from hours (e.g., trash compactor) to seconds (e.g., parking meter) to milliseconds or less (e.g., factory floor sensing and control). With all of the possible variations, it is important to have flexible yet accurate test facilities for these devices.

Modern slavery and the employment relationship: Exploring the continuum of exploitation

The term ‘modern slavery’ constitutes a broad non-legal umbrella term that refers to a range of abusive practices including, but not limited to, forced labour, bonded labour, human trafficking and child slavery. While the most severe forms of labour exploitation represent instances of modern slavery, focusing on labour abuses more broadly is also important as it is not always clear at what point non-compliance with labour standards seeps into cases of criminal exploitation. This Special Issue focuses on what the large- and small-scale risk factors are that can cause working conditions to deteriorate, on how people can become trapped in exploitative conditions and on what can be done to prevent and remedy labour abuses. It does this by exploring the macro-level, specifically by examining global value chains and the labour exploitation within the global production regime; by exploring the meso-level, by focusing on the market-based character of business and human rights regulation; and by looking at the micro-level by examining labour regimes on factory floors and in private residences.

Performance analysis and optimisation of Bernoulli serial production lines with dynamic real-time bottleneck identification and mitigation

With the rapid advances of Industry 4.0 technologies, developing rigorous, model-based algorithms for production system performance metrics calculation, control, and optimization has become a critical task to inject intelligence into the smart manufacturing practice, thus facilitating automated decision-making on the factory floor. This paper is intended to contribute to this area. Specifically, we consider serial production lines with finite buffers and machines following the Bernoulli reliability model. In addition, we assume that one can dynamically control the allocation of a shared workforce via real-time production bottleneck identification and mitigation. We first derive formulas to calculate the performance metrics of two-machine systems. Then, we extend the results to multi-machine cases by developing an aggregation-based analytical algorithm, whose accuracy is verified using numerical experiments. Based on this performance evaluation method, we study the optimization of the control policy. In particular, a space reduction technique is applied that decomposes the system into several sub three-machine lines and search algorithms are proposed to identify a good-quality control policy in the reduced policy space. Numerical experiments are used to demonstrate the efficacy of the optimized policy. An illustrative example is given to provide insights into the structure and operation of an effective control policy.

Neo-Imperialism and the Precarious Existence of Vietnamese Factory Workers During the Covid-19 Lockdowns in 2021

Based on interviews with Vietnamese factory workers we discuss the impact Covid lockdowns had on their lives and illuminate how fragile their economic circumstances are in general. Both the government and major international corporations, such as Samsung and Nike, took extraordinary steps to keep workers on factory floors when covid infections started spreading in 2020. The government and businesses pressed laborers to work, sleep, and eat in their factories to stop the spread of the virus and to keep production lines moving. There was a determined push to get people vaccinated. It wasn’t just the Vietnamese government that tried to get jabs in arms; ninety U.S. corporate executives urged the U.S. government to speed vaccine delivery to the country. Japanese, South Korean, and other Southeast Asian companies located in Vietnam also joined in these efforts. The purported reason was that supply chains had been disrupted by covid and exporters feared they would not have products on the shelves for the coming holiday season. We argue that focusing on supply chain disruptions obscures the fact that what is being transferred between developing countries and those in the core is not just television sets and tennis shoes but human labor power. It is a form of economic imperialism in which countries no longer conquer another nation to extract wealth but operate through international corporations unfettered by ties to any specific country. The Vietnamese government offers international corporations significant tax breaks and other benefits to set up shop in industrial zones. Their profit margins are high and come at the expense of workers, who must work overtime and enlist other family members in their labor force to survive. We conclude by identifying actions the Vietnamese government could take to alleviate the plight of factory workers.

Selection of optimal machine learning algorithm for autonomous guided vehicle’s control in a smart manufacturing environment

Artificial intelligence is a field of research that is seen as a means of realization regarding digitalization and industry 4.0. It is considered as the critical technology needed to drive the future evolution of manufacturing systems. At the same time, autonomous guided vehicles (AGV) developed as an essential part due to the flexibility they contribute to the whole manufacturing process within manufacturing systems. However, there are still open challenges in the intelligent control of these vehicles on the factory floor. Especially when considering dynamic environments where resources should be controlled in such a way, that they can be adjusted to turbulences efficiently. Therefore, this paper aimed to develop a conceptual framework for addressing a catalog of criteria that considers several machine learning algorithms to find the optimal algorithm for the intelligent control of AGVs. By applying the developed framework, an algorithm is automatically selected that is most suitable for the current operation of the AGV in order to enable efficient control within the factory environment. In future work, this decision-making framework can be transferred to even more scenarios with multiple AGV systems, including internal communication along with AGV fleets. With this study, the automatic selection of the optimal machine learning algorithm for the AGV improves the performance in such a way, that computational power is distributed within a hybrid system linking the AGV and cloud storage in an efficient manner.

An exploration of effective supervisory engagement in the clothing industry through activity sampling technique

The gradual financial decrease through national and international competition led approximately 50% of clothing manufacturers to shut down their businesses in the past decade. In a grapple for improved productivity, organisations are evaluating human assets for further value-add. Industry 4.0 embraces total interaction of technology and human resources with a view to a multi-skilled environment. In this endeavor, first-line managers (supervisors) play a critical role in the clothing manufacturing industry in terms of the elimination of non-value-added activities. The meteoric rise of technology-driven processes inculcated in the drive of Industry 4.0. The clothing industry lacks the drive for continuous improvement due to an impasse in skills-driven improvement and the application of industrial engineering principles. Organisations are seeking improvement opportunities in multi-skilling the workforce. In this endeavor, supervisory activities were evaluated to determine value-add in the production process. This study aims to evaluate supervisory engagement to ascertain non-value-added activities and forms a foundation to leverage human capital into competitive advantage. The research adopted the application of activity sampling analysis through a case study at a clothing manufacturer. Direct observation and informal discussions on the factory floor were used as the primary means for data collection. Keywords supervisory engagement; activity sampling; industrial engineering

Scheduling para Manufatura Aditiva: uma revisão da literatura

Abstract: Advancements in production technologies and materials have facilitated the use of additive manufacturing (AM) (i.e., 3D printing) in the large-scale production of finished products with high level of customization, simplification of the factory floor, and fast delivery. Production sequencing is a well-established topic in this research area; however, its application to an AM environment suffers from specific issues that are yet to be explored. This paper presents a systematic literature review for mapping the state-of-the-art production sequencing methods in AM and for discussing the content of 26 articles published in magazines between 2017–2020. The main mathematical models, algorithms adopted for their solution, and main characteristics of computational experiments performed in these articles are identified; the results indicate that some characteristics of the problem can still be included in these models, such as the possibility of outsourcing and technology restrictions, which are yet to be explored in the literature. Further, authors observed the need for more robust computational experiments to better evaluate the proposed solutions.

A cyber-physical system approach to zero-defect manufacturing in light-gauge steel frame assemblies

Recent advances in manufacturing research have set the stage for the industrial integration of zero-defect manufacturing strategies, aiming towards a more sustainable production paradigm. A systematically deployment guideline to implement zero-defect manufacturing is needed to transform the future cyber-physical factory floor. This paper describes a novel framework based on a well-known cyber-physical architecture that provides advanced information analytics, robust information flows, and data acquisition systems that support defect detection and prediction introduces repair technologies and sets up procedures for preventive maintenance. Through continuous inspection of product and equipment status during the manufacturing process, raw quality and tool health data from different sources is used to obtain key performance indicators. Statistical tools such as cross-correlation are then applied to quantify underlying relationships between product quality specifications and equipment health. The resulting correlations are then used to reduce non-conformance of products manufactured by implementation of preventive maintenance. A unified implementation for zero-defect manufacturing cyber-physical processes eases their integration in future Industry 4.0 facilities and validated in the context of offsite construction manufacturing of steel frame assemblies.

My Brother’s New Clothes

A personal narrative about the dressed body of the Other, in a play with the multiple meanings of the terms and concepts involved in the manufacture of the “marielito” as assigned identity whose attributes are intricately linked to the way in which that othered body is outfitted, shrouded and clothed, both figuratively and metaphorically. In a hypothetical, one-sided dialog with the “marielito” figure of her childhood imaginary, the author stitches together a loose collection of imprints from early 1980s Miami, present-day reflections and retrospective impressions from her young adulthood—church clothing drives and donations, garment factory floors, news media images, styles, accessories, garments, branding, films, fear, moralism, family conflict—intertwining and interweaving these fragments to create the identitary patchwork of otherness that reveals the social underpinnings of stigmatization.

Dynamic performance prediction in flexible production lines with two geometric machines

Due to the intelligent manufacturing strategies deployed and being implemented in recent years, flexible production is widely used on the factory floor at present. While most of the existing investigations are concerned with the steady-state of systems, very few results have been published on systems' dynamic behaviour. However, since flexible production is sometimes carried out according to customised orders, most of which are in relatively medium or even small sizes, part or all the production of such systems are in the dynamic process. As a result, the dynamic characteristics of production systems are of significant importance. Meanwhile, dynamic performance is regarded as an important direction in the research of manufacturing systems. In this work, for serial flexible production lines with two geometric machines and one finite buffer, we study the problems of dynamic performance evaluation, system behavioural properties, and energy-efficient operation control. Specifically, the model of production lines under consideration is formulated. Then, an analytical method to assess the dynamic performance of such flexible production lines is proposed. Moreover, the behavioural properties of the systems are also investigated. Finally, we study the problem of control parameters selection for the system under operation control.

Data rich, information poor

Data rich, information poor

Review: The Palestinian Idea: Film, Media and the Radical Imagination, by Greg A. Burris

Review: The Palestinian Idea: Film, Media and the Radical Imagination, by Greg A. Burris

Analyzing the Vibration Exposure to the Safety and Health at Workplace: A Case in the Urea Granulation Unit of the Fertilizer Factory

This study aims to evaluate the vibration exposure experienced by workers in the Urea Granulation Screen Unit (UGSU) at the fertilizer factory in Aceh, Indonesia. This study involved 30 labors in charge as operators, mechanical maintenance officers, electrical maintenance officers, instrument maintenance officers, and inspectors. The measurement of vibration was carried out using a Triaxial Accelerometer with Integral Magnet and shows that the vibration exposure on the factory floor of the urea granulation screen unit occurs vertically with a minimum value of 0.298 m/s2 and a maximum of 1.630 m/s2. According to ISO 2631-1:1997, the maximum vibration values that occur are categorized as a likely health risk zone and result in uncomfortable reactions to the workers. Furthermore, this study analyzes the effect of vibrations on musculoskeletal problems using a Nordic Body Map (NBM) questionnaire. It reveals that the average score of musculoskeletal complaints is 71.6, which defines a high degree of pain. The results of the NBM questionnaire also showed that the vulnerable part of the body which experienced musculoskeletal complaints is the knee. The result of vibration exposure on this body part shows the highest value of 3.437 m/s2. To minimize occupational diseases and accidents, it is necessary to manage a working system that takes into account legal standards, ideal working time, and working shifts in the work area.

A contextual sensor system for non-intrusive machine status and energy monitoring

Event-driven contexts in manufacturing occur pervasively as a result of interactions among involved entities such as machines, workers, materials, and environment. One of the primary tasks in smart manufacturing is to derive a context-aware system conveniently incorporating worker knowledge for generating timely actionable intelligence for workers on factory floor and supervisors to respond. In this paper, we propose to design a human-and-machine interaction recognition framework by using a causality concept to collect contextual data for classifications of normal and abnormal machine operations. The causes and effects are between workers and machines for this initial research. To apply the causality to recognize worker interactions, initially a reliable way to identify the states of machines is necessary. The proposed contextual sensor system, consisting of a power meter for measuring machine operation conditions, a visual camera for capturing worker and machine interactions via a finite state machine model, and an algorithm for determining power signatures of individual components via energy disaggregation is implemented on semiconductor fabrication machines (manual or PLC controlled) each with multiple components. The experiment results demonstrate its context extraction capability such as components states and their corresponding energy usage in real time as well as its ability to identify anomalous operation conditions.

Ladies Aid as Labor History

AbstractIn the Arabic-speaking mahjar (diaspora), the plight of the working poor was the focus of women’s philanthropy. Scholarship on welfare relief in the interwar Syrian, Lebanese, and Palestinian diaspora currently situates it within a gendered politics of benevolence. This article reconsiders that frame and argues for a class-centered reassessment of “ladies aid” politics exploring the intersections of women’s relief with proletarian mutual aid strategies. Founded in 1917, the Syrian Ladies Aid Society (SLAS) of Boston provided food, shelter, education, and employment to Syrian workers. SLAS volunteers understood their efforts as mitigating the precarities imposed on Syrian workers by the global capitalist labor system. Theirs was both a women’s organization and a proletarian movement led by Syrian women. Drawing from SLAS records and the Syrian American press, the article centers Syrian American women within processes of working-class formation and concludes that labor history of the interwar mahjar requires focus on spaces of social reproduction beyond the factory floor.

Lula and His Politics of Cunning: From Metalworker to President of Brazil

Lula and His Politics of Cunning: From Metalworker to President of Brazil

Understanding vulnerabilities in cyber physical production systems

ABSTRACT Development of future manufacturing systems is featured with flexibility, mass customization, intelligence and context based learning to produce smart products. These production systems are characterized through networked, cooperating objects called cyber physical systems (CPSs). From the manufacturing perspective, the ability to communicate data and develop interaction between devices, manufacturing machinery, raw materials, working robots, humans and the plant environment develops the concept of cyber physical production systems (CPPS). Human-robot collaboration is a technology area that will be an integrated part of the future factory floor and the CPPS. With the involvement of human part in the automated system industrial scenarios, practical safety issues are expected to arise in the connected environment due to the use of a large number of devices, sensors, and cloud services causing complex network, IP conflicts, compromised nodes and communication issues. This all may lead to occupational safety issues on the factory floor in different ways and combinations. Overall, the system’s physical vulnerability will be increased in the context of compromised connected working space and cyber-security. In this paper, the authors developed a risk assessment based on system vulnerability of a CPPS developed for a use case requirement and performed a simulated approach by launching a cyber-attack and measuring the causal effect to identify implications on human worker safety.

Control Strategy for Jam and Wedge-Free 3D Precision Insertion of Heavy Objects Suspended With a Multi-Cable Crane

Overhead cranes have been used extensively in heavy industry for transporting heavy objects across a factory floor. This work aims to make such cranes more dexterous and capable of performing precision assembly tasks by suspending an object with tension-controlled cables. New control strategies are presented for coordinating multiple winches affixed to a crane, so that a) a suspended shaft (peg) can be smoothly inserted into a hole without jamming despite a small clearance, and b) even in the case a shaft gets wedged inside a hole, the shaft can be recovered from wedging. It is shown through analysis, and validated with experiments, that simply equalizing the three cable tensions allows the shaft to be inserted smoothly into a hole. If the difference between the cable tensions is large, the shaft may experience large contact frictional forces, which may cause the shaft to jam. If wedging occurs, two particular proportions of cable tensions are obtained to break wedging. A process monitor is designed to detect wedging, estimate the location and orientation of the shaft wedged within the hole, and confirm whether the shaft has recovered from wedging. The tilt of the shaft can then be adjusted and re-insertion can occur. The effectiveness of the proposed control strategies are validated on a 3D multi-cable crane prototype that is able to demonstrate the successful insertion of a 15 kg shaft into a hole with 120 μm of clearance.

Metric-based approach to assess sustainable manufacturing performance at manufacturing process levels

ABSTRACT As new technologies have been changing the production scenario, sustainable production practices stand out as possible solutions to harmonise industrial activities and biodiversity conservation for the benefit of humanity. In this context, a proposal based on the concepts of the Triple Bottom Line for evaluating sustainability index will be presented in order to fill in some gaps in the literature on models for evaluating sustainability indices. The methodological approach consists of developing sustainability indicators (KPI) which has been the basis for measuring the sustainability index. To verify the applicability of this model, two companies which apply metallic coating on rolls of sugar cane mills were assessed. According to the results, it was possible to measure the sustainability level of each KPI, of the pillars and the general sustainability index. The proposal stands out from other models because it allows: a) assessment of each stage of the production process, b) application flexibility regardless of the type of the process, c) measurement flexibility according to the companies’ needs, d) ease and speed of execution on the factory floor, e) possibility of computerisation.