Effect of lean manufacturing tools on sustainability: the case of Mexican maquiladoras.

The Mexican maquiladora industry is applying Lean Manufacturing Tools (LMT) in its production lines; however, few studies have investigated its relationship with sustainability (social, economic, and environmental). This paper presents a second-order structural equation model (SEM) relating 8 LMT integrated into three independent latent variables: continuous improvement (Kaizen and Gemba), supporting tools (Andon, visual management, and Poka-yoke), and machinery and equipment (total productive maintenance, overall equipment effectiveness, and Jidoka) that are related to social, economic, and environmental sustainability as dependent variables. The model is validated with information obtained from 249 companies using partial least squares. Findings show that the application of LMT in the Mexican maquiladora industry avoids the generation of waste and reprocessing. Likewise, the improvement of production processes reduces the waste emitted into the environment and reduces energy consumption. Also, when companies have environmental programs, the work environment is safe, and labor relations are improved, increasing morale and the commitment to work for the company, gaining economic and ecological benefits.

Determining optimal laser-beam cutting equipment investment through a robust optimization modeling approach.

The acquisition of Advanced Manufacturing Technologies (AMT), such as high-power fiber or CO2 laser cutting equipment, generally involves high investment levels. Its payback period is usually more extended, and there is a moderate-to-high risk involved in adopting these technologies. In this work, we present a robust model that optimizes equipment investing decisions, considers the process's technical constraint and finds an optimal production plan based on the available machinery. We propose a linear investment model based on historical demand information and take physical process parameters for a LASER cutting equipment, such as cutting speed and gas consumption. The model is then transformed into a robust optimization model which considers demand uncertainty. Second, we determine the optimal production plan based on the results of the robust optimization model and assuming that demand follows a normal distribution. As a case study, we decided on the investment and productive plan for a company that offers Laser-Beam Cutting (LBC) services. The case study validates the effectiveness of the proposed model and proves the robustness of the solution. For this specific application of the model, results showed that the optimal robust solution could increase the company's expected profits by 6.4%.

Recognition of industrial machine parts based on transfer learning with convolutional neural network.

As the industry gradually enters the stage of unmanned and intelligent, factories in the future need to realize intelligent monitoring and diagnosis and maintenance of parts and components. In order to achieve this goal, it is first necessary to accurately identify and classify the parts in the factory. However, the existing literature rarely studies the classification and identification of parts of the entire factory. Due to the lack of existing data samples, this paper studies the identification and classification of small samples of industrial machine parts. In order to solve this problem, this paper establishes a convolutional neural network model based on the InceptionNet-V3 pretrained model through migration learning. Through experimental design, the influence of data expansion, learning rate and optimizer algorithm on the model effectiveness is studied, and the optimal model was finally determined, and the test accuracy rate reaches 99.74%. By comparing with the accuracy of other classifiers, the experimental results prove that the convolutional neural network model based on transfer learning can effectively solve the problem of recognition and classification of industrial machine parts with small samples and the idea of transfer learning can also be further promoted.

Effect of neck posture on cervicothoracic loads in overhead crane operators.

Awkward neck postures are commonly documented to be associated with an increased risk of neck disorders. This study intended to continuously monitor and evaluate neck postures and to estimate the cervicothoracic loads among overhead crane operators during work time. Neck postures were measured among 40 randomly selected operators by an inclinometer during 2 h of work time. To determine the tasks and adapt the posture recordings to each of their corresponding tasks, direct observation was conducted concurrently. The median neck flexion and lateral bend angles were 28.23° and 11.30°, respectively. The mean compression and shear loads on the neck ranged from 75.22 to 113.14 N and from 9.50 to 41.11 N, respectively. The results indicated substantial levels of exposure to awkward and extreme neck postures among the operators. The nature of the operators' work and the visual requirements of some tasks will increase the mechanical loads on the neck.

Optimization design of a novel X-type six-high rolling mill based on maximum roll system stiffness.

The present investigation devices a novel X-type six-high (X-6h) mill. In addition, parametric models of different roll layouts such as the four-high (4-h), I-type six-high (I-6h), and X-6h mills are established. Three-dimensional (3D) finite element (FE) contact analysis for a strip rolling process is conducted when the mills are subjected to a constant vertical load of 65 kN. Through comparative analysis of von Mises stress, contact stress and elastic deformation displacement in three roll layouts, the rigidity characteristic of each is obtained, and it is found that the proposed X-6h mill has the largest roll gap stiffness. The influence of different roll diameter ratios on the roll gap stiffness of the roll system is investigated, based on which an optimization design model is built. Further, by taking into account the roll gap stiffness of the roll system as the optimization objective, the optimum diameter ratios of backup roll (BUR) to work roll (WR) of the X-6h rolling mill is achieved via the genetic algorithm (GA) optimization method, obtaining the optimum structural parameters of BUR and WR as well. The reliability of the proposed design is verified by manufacturing a prototype mill which produced magnesium alloy and aluminum alloy strips of high quality.

Research on the energy-saving control strategy of a belt conveyor with variable belt speed based on the material flow rate.

Aiming at solving the problem of high energy consumption in the rated belt speed operation of a belt conveyor system when the material flow rate is reduced, the power consumption of the frequency converter, motor, and belt conveyor is analyzed, a power consumption model of the belt conveyor system is established, the relationship between the power consumption of the belt conveyor system and belt speed is obtained, and a energy-saving control strategy of the belt conveyor with variable belt speed based on the material flow rate is put forward. The energy consumption of the belt conveyor is analyzed for a practical case. Results show that the power consumption model is accurate and the control strategy effectively reduces energy consumption. The model has high application value in coal, ports, power, mine, metallurgy, chemical, and other industries.

Characterizing particle emissions from a direct energy deposition additive manufacturing process and associated occupational exposure to airborne particles.

This study aims to characterize airborne particles emitted from a metal additive manufacturing machine and related levels of occupational exposure. To achieve this, a complete measurement methodology was deployed around a direct energy deposition machine. Different operating conditions were investigated, based on configurations of two materials and two injection nozzles. Two replicates were performed for each condition. Airborne particles emitted during repeated manufacturing cycles were measured simultaneously at the source, in the near field, in the far field and on the operator. Real-time instruments were used to characterize the machine emissions (10 nm-10 µm) associated with respirable and inhalable samplers and cascade impactors. Measurements were made during both the manufacturing process and transient operating phases. In parallel, personal exposure to hexavalent chromium was assessed. The number of particles measured for the different machining phases show that high levels of particles (> 5 × 105 # cm-3, 0.3-1.3 mg m-3 inhalable particles, 0.2-6 µg m-3 CrVI) were emitted in the machine enclosure. The size distributions indicate that more than 90% of the particles are smaller than 250 nm. Occupational exposure to CrVI was found to be below the LOQ of 0.098 µg m-3 for the two alloys investigated. During the machining process, near-field number and mass concentrations were ∼ 104 # cm-3, and below 0.04 mg m-3, respectively. Far-field number concentrations were also on the order of 104 # cm-3 throughout the whole monitoring period. The transient phase of door opening was found to result in high levels of exposure (> 105 # cm-3), which were also detected in the near-field, confirming the need to implement preventative actions. To address this issue, a collective protective measure, consisting of setting a time delay of about 8 min between the end of the manufacturing process and opening of the door, could be employed. This collective measure should also be accompanied by the wearing of personal protective equipment by the operator when an intervention in the machine enclosure is necessary.

Prediction of formation force during single-point incremental sheet metal forming using artificial intelligence techniques.

Single-point incremental forming (SPIF) is a technology that allows incremental manufacturing of complex parts from a flat sheet using simple tools; further, this technology is flexible and economical. Measuring the forming force using this technology helps in preventing failures, determining the optimal processes, and implementing on-line control. In this paper, an experimental study using SPIF is described. This study focuses on the influence of four different process parameters, namely, step size, tool diameter, sheet thickness, and feed rate, on the maximum forming force. For an efficient force predictive model based on an adaptive neuro-fuzzy inference system (ANFIS), an artificial neural network (ANN) and a regressions model were applied. The predicted forces exhibited relatively good agreement with the experimental results. The results indicate that the performance of the ANFIS model realizes the full potential of the ANN model.

Parallelism between risk and perception of risk among caregivers during anesthesia delivery.

The paper examines the different perceptions of risk associated with anesthesia systems from the viewpoint of the product manufacturer and the caregiver. Only a little research has been done with regard to the impact of perception of risk on patient safety in anesthesia. The role of the manufacturer in mitigating the perception of risk will be central for the work. The risk will be examined as the probability of negative occurrences based on the Medical Device Reportable (MDR) events for 2016 and 2017 and it will be examined how the caregiver perceives and manages these risks when delivering anesthesia. Analysis of the manufacturer's public Medical Device Reportable events data will be performed in the US market and will represent the actual risk achieved; this review will provide a perspective on how the risk is perceived and managed by the caregiver when delivering anesthesia. The goals of the paper are to highlight how the role of the manufacturers can have an impact on the reduction of perception of risk, increasing patient safety, and showing how the perception of risk is usually magnified by the hospital personnel.

Production quality and human factors engineering: A systematic review and theoretical framework.

The purpose of this paper is to systematically examine available empirical evidence on the impact of human factors (HF) in the design and management of manufacturing operations on system quality performance. A systematic review was conducted to map the linkages between the human-system fit in the design of operations systems (OS) with production quality. A total of 73 empirical studies were identified linking HF to OS performance in manufacturing. Quality risk factors included HF aspects in product design, process design and workstation design of the manufacturing OS. Quality deficits were associated with undesirable human effects of workload like fatigue and injury-related risk factors. Forty-six percent of the studies reported on efforts to improve HF in the OS with effect sizes for quality improvements reaching up to 86%. The paper documents available quality risk factors in the design of OS. It also provides a conceptual framework explaining HF-Quality linkage.

Full shift assessment of back and head postures in overhead crane operators with and without symptoms.

OBJECTIVES: Prolonged sitting with a flexed back and neck is recognized as being associated with an increased risk of neck and back pain disorders among overhead crane operators. The aim of this study was to compare back and head postures over a full shift of work between operators who experience back and neck pain, and healthy operators. METHODS: In a first phase, the prevalence of musculoskeletal symptoms was assessed using the Nordic questionnaire among 120 crane operators. Based on first phase results, 17 operators with back/neck disorders were matched with 15 healthy operators based on age and selected to participate in the second phase of the study. Postures and movements were continuously measured over an 8 h shift using inclinometers. RESULTS: The highest 12-month prevalence of musculoskeletal disorders was found in the lower back, neck and knees. Case and control groups differed significantly in back and head flexion angles at the 50th percentiles APDF (p < 0.05). There was also a significant difference in the time spent working in an extreme posture of the back and head between groups (p < 0.05). CONCLUSIONS: This is the first study to document work postures assumed during a full work shift and to compare postures between symptomatic and healthy overhead crane operators. Physical exposure in case group operators was characterized by more awkward and extreme postures in the back and head. The results of this study demonstrate that effective prevention strategies directed towards musculoskeletal disorders are required that address awkward work postures for overhead crane operators.

The Dibber: Designing a standardised handheld tool for lay-up tasks.

We present an application of engineering and ergonomics principles in the design of a standardised tool, The Dibber, which is a tool with multiple geometric features to fit the diversity of lay-up tasks used in the composites industry. The Dibber is the result of a design process, which consists of a series of observations and prototyping to extract geometric requirements for lay-up tasks. To demonstrate that it is possible to design a standardised tool prototypes of the Dibber were distributed and 91 participants gave feedback. Our results are positive and show consistent patterns of use across industry sectors, as well as between novice and expert laminators.

Human-centered design (HCD) of a fault-finding application for mobile devices and its impact on the reduction of time in fault diagnosis in the manufacturing industry.

The present article describes the design process of a fault-finding application for mobile devices, which was built to support workers' performance by guiding them through a systematic strategy to stay focused during a fault-finding process. In collaboration with a project partner in the manufacturing industry, a fault diagnosis application was conceptualized based on a human-centered design approach (ISO 9241-210:2010). A field study with 42 maintenance workers was conducted for the purpose of evaluating the performance enhancement of fault finding in three different scenarios as well as for assessing the workers' acceptance of the technology. Workers using the mobile device application were twice as fast at fault finding as the control group without the application and perceived the application as very useful. The results indicate a vast potential of the mobile application for fault diagnosis in contemporary manufacturing systems.

Predicting tool operator capacity to react against torque within acceptable handle deflection limits in automotive assembly.

The proportion of tool operators capable of maintaining published psychophysically derived threaded fastener tool handle deflection limits were predicted using a biodynamic tool operator model, interacting with the tool, task and workstation. Tool parameters, including geometry, speed and torque were obtained from the specifications for 35 tools used in an auto assembly plant. Tool mass moments of inertia were measured for these tools using a novel device that engages the tool in a rotating system of known inertia. Task parameters, including fastener target torque and joint properties (soft, medium or hard), were ascertained from the vehicle design specifications. Workstation parameters, including vertical and horizontal distances from the operator were measured using a laser rangefinder for 69 tool installations in the plant. These parameters were entered into the model and tool handle deflection was predicted for each job. While handle deflection for most jobs did not exceed the capacity of 75% females and 99% males, six jobs exceeded the deflection criterion. Those tool installations were examined and modifications in tool speed and operator position improved those jobs within the deflection limits, as predicted by the model. We conclude that biodynamic tool operator models may be useful for identifying stressful tool installations and interventions that bring them within the capacity of most operators.

Market Competitiveness Evaluation of Mechanical Equipment with a Pairwise Comparisons Hierarchical Model.

This paper provides a description of how market competitiveness evaluations concerning mechanical equipment can be made in the context of multi-criteria decision environments. It is assumed that, when we are evaluating the market competitiveness, there are limited number of candidates with some required qualifications, and the alternatives will be pairwise compared on a ratio scale. The qualifications are depicted as criteria in hierarchical structure. A hierarchical decision model called PCbHDM was used in this study based on an analysis of its desirable traits. Illustration and comparison shows that the PCbHDM provides a convenient and effective tool for evaluating the market competitiveness of mechanical equipment. The researchers and practitioners might use findings of this paper in application of PCbHDM.

An investigation of safety design practices of metal machines.

BACKGROUND: Machinery safety issues are a challenge facing manufacturers who are supposed to create and provide products in a better and faster way. In spite of their construction and technological advance, they still contribute to many potential hazards for operators and those nearby. OBJECTIVE: The aim of this study is to investigate safety aspects of metal machinery offered for sale on Internet market according to compliance with minimum and fundamental requirements. METHODS: The study was carried out with the application of a checklist prepared on the basis of Directive 2006/42/EC and Directive 2009/104/EC and regulations enforcing them into Polish law. RESULTS: On the basis of the study it was possible to reveal the safety aspects that were not met in practice. It appeared that in the case of minimum requirements the most relevant problems concerned information, signal and control elements, technology and machinery operations, whereas as far as fundamental aspects are concerned it was hard to assure safe work process. CONCLUSIONS: In spite of the fact that more and more legal acts binding in the Member Countries of the European Union are being introduced to alleviate the phenomenon, these regulations are often not fulfilled.

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

Study on a Mechanical Semi-Active Heave Compensation System of Drill String for Use on Floating Drilling Platform.

There are some disadvantages for existing heave compensation systems of drill string used for the Floating Drilling Platform (FDP), including high energy consumption, large and complex structure, and expensive manufacturing and maintenance costs. In view of the above, we present a streamlined mechanical semi-active heave compensation system (MSAHC) in this study. This system consists of active compensation part with the pinion and rack and passive compensation part. In order to evaluate system performance of the MSAHC, we establish its simulation model with AMEsim software. In the process of simulation, displacement of rotary hook and energy consumption is regarded as performance parameters of the system. And the change rule of two performance parameters are analyzed by changing these design parameters including gear radius of the pinion and rack, scale coefficient of PID, rotary hook load, heave height and heave period of the FDP, and accumulator volume. Then, based on the simulation results of the MSAHC system performance, we have selected out a best set of design parameters from them. Moreover, the feasibility of the design scheme of the MSAHC is effectively verified by comparison with the existing three heave compensation system. The result shows that the energy consumption of the MSAHC is lower than the active heave compensation system (AHC) and the semi-active heave compensation system (SAHC) when achieving a same compensation effect as well as the accumulator volume of MSAHC is half of the passive heave compensation system (PHC). Therefore, the new designed MSAHC not only ensure compensation effect but also lower energy consumption, and its structure is simplified by adopting the simple mechanical structure to decrease manufacturing cost, maintenance cost and floor space.

Objective classification of performance in the use of a piercing saw in jewellery making.

Data from 15 jewellery students, in their 1st and 3rd years of training, were analysed to show how data collected from work settings can be used to objectively evaluate performance in the use of tools. Participants were asked to use a piercing saw to cut 5 lines in a piece of metal. Performance was categorised in terms of functional dynamics. Data from strain gauges and a tri-axial accelerometer (built into the handle of the saw) were recorded and thirteen metrics derived from these data. The key question for this paper is which metrics could be used to distinguish levels of ability. Principal Components Analysis identified five components: sawing action; grasp of handle; task completion time; lateral deviation of strokes; and quality of lines cut. Using representative metrics for these components, participants could be ranked in terms of performance (low, medium, high) and statistical analysis showed significant differences between participants on key metrics.