Research Trends and Outlooks in Assembly Line Balancing Problems

This paper presents the findings from the survey of articles published on the assembly line balancing problems (ALBPs) during 2014-2018. Before proceeding a comprehensive literature review, the ineffectiveness of the previous ALBP classification structures is discussed and a new classification scheme based on the layout configurations of assembly lines is subsequently proposed. The research trend in each layout of assembly lines is highlighted through the graphical presentations. The challenges in the ALBPs are also pinpointed as a technical guideline for future research works

Facility Location Placement Optimisation for Bagged Cement Distribution During the COVID-19 Pandemic

This study was based on a challenge that one of Thailand's cement companies encountered in 2021 as a result of fierce competition in the Northeastern region and falling market share during the COVID-19 pandemic. Without a doubt, the management of supply chains played an essential role in this issue. As a result, this research addressed the company's distribution strategy by attempting to determine a new location for the distribution centre to achieve two conflicting objectives at the same time, namely, minimising total transportation cost and maximising service level (delivery lead time reduction). For the problem at hand, a linear programming model was developed. Once different options were identified, the pros and cons of each approach were evaluated, and then the distribution strategy was altered to meet the actual conditions. It was discovered that changing distribution centres in some locations was a successful strategy for shortening delivery lead times with an opportunity to achieve a 22% improvement in service level while still controlling transportation expenses prior to arriving at the end customers not beyond the target at 15% increased from the current strategy

Solving Many-Objective Car Sequencing Problems on Two-Sided Assembly Lines Using an Adaptive Differential Evolutionary Algorithm

The car sequencing problem (CSP) is addressed in this paper. The original environment of the CSP is modified to reflect real practices in the automotive industry by replacing the use of single-sided straight assembly lines with two-sided assembly lines. As a result, the problem becomes more complex caused by many additional constraints to be considered. Six objectives (i.e. many objectives) are optimised simultaneously including minimising the number of colour changes, minimising utility work, minimising total idle time, minimising the total number of ratio constraint violations and minimising total production rate variation. The algorithm namely adaptive multi-objective evolutionary algorithm based on decomposition hybridised with differential evolution algorithm (AMOEA/D-DE) is developed to tackle this problem. The performances in Pareto sense of AMOEA/D-DE are compared with COIN-E, MODE, MODE/D and MOEA/D. The results indicate that AMOEA/D-DE outperforms the others in terms of convergence-related metrics

Practical Implementation of Lean Management Techniques and Ergonomic Consideration to Improve Manual Assembly Process During the COVID-19 Crisis

This research focused on the cycle time reduction of the automotive audio monitor base frame assembly process in a small electronic parts manufacturing company through the application of the Lean and ergonomics approaches. In recent years, the company has faced the problem of not being able to assemble products to meet customers’ orders due to the need to lay off some skilled workers to survive during the COVID-19 crisis. This resulted in a severe loss in customer goodwill and confidence. The improvement process began with a review of the current assembly workflow as well as the detailed hand and arm movements of workers. Then, to determine the as-is operational procedure and average cycle time of the assembly process, a series of videos were recorded and playback in slow motion. Lean management techniques, such as 7 wastes and 5 Whys, were employed to identify the potential root causes of the problems. In addition, the ECRS (eliminate, combine, rearrange and simplify) techniques of Lean management in combination with the ergonomics principles were applied to modify the operational procedure and the postures and movements of the workers. The workspace and environmental conditions were also adjusted to enable more efficient workers’ operations. The result demonstrated that such an approach could help reduce the cycle time of the assembly process to achieve the predefined target

The Impact of Walking Time on U-Shaped Assembly Line Worker Allocation Problems

The one-piece flow manufacturing line of single and customized products is usually organized as a U-shaped assembly layout. In this study, the characteristics of a single U-line are described and modeled. The worker allocation problem is hierarchically concerned with the task assignment into a U-line and allocate task to workers in sequence. Several products are assembled in 7-task to 297-task problems, and each problem is performed with a given cycle time. The primary purpose is to identify the impact of walking time on both symmetrical and rectangular U-shaped assembly layouts. The minor purpose is to compare the number of workers between two fixed layouts. Coincidence algorithm demonstrates clarifying solutions. To respond to two previous aims, the primary objective function of a number of workers is used. Finally, with the Pareto-optimal frontier between the deviation of operation times of workers and the walking time, its computational study is exemplified to identify good task assignment and walking path

The Impact of Organisational Climate on Employee Engagement and Performances in a Multinational Oil and Gas Exploration and Production Company in Thailand

This research aims to support the company to improve employee engagement by exploring antecedent issues that have not been previously captured by the company survey. Organisation climates are chosen since they focus on intrinsic values such as purpose and work harmony, i.e. internal communication, learning and development, and perceived organisation support, to close the engagement gap and translate them into feasible actions. In addition, the study further explores the performance indicator beyond conventional measures. Conventionally, the benefit of engagement is measured through self-rating questions, e.g. organisational commitment and job satisfaction. However, it lags off the link between those measurements and tangible benefits. The internal survey data are analysed by the structural equation model (SEM) to identify the relationship between antecedents and consequences, and then linear regression is applied to correlate each factor to the observed performance. To provide a complete understanding of each relationship, interviews are conducted to find an insightful view of the model outcome. The result emphasises the strong relationship between engagement and organisational commitment, especially organisation engagement. Learning and development show contradicting results from the previous study and the outcome cannot clear the myth that higher engagement leads to better performance but it has shown a promising correlation between engagement and performance. The finding could help the management team and HR department better understate the priority for each antecedent which also links to the benefits of engagement that ultimately supports future HRM

Opportunities and Barriers to the Adoption of Blockchain-Based Games in an Online Gaming Company in Thailand

This research aims to explore potential opportunities and barriers related to the adoption of blockchain-based games in an online gaming company in Thailand. The identified opportunities are classified under the benefits framework proposed by Shang and Seddon [1], and the identified barriers are classified under the Technology-Organisation-Environment (TOE) framework. Based on the knowledge and experience of experts in the case company, all the opportunities and barriers are then assessed using the concept of Failure Mode and Effect Analysis (FMEA), which is further improved using the Analytic Hierarchy Process (AHP) by assigning a relative weight to each element of the FMEA before being used to find the priority number (PN). Next, the Pareto principle is applied to reveal the critical opportunities and barriers. As a result, a total of 21 critical opportunities are revealed and categorised into 5 dimensions: 4 operational opportunities; 3 managerial opportunities; 7 strategic opportunities; 4 infrastructure opportunities; and 3 organisational opportunities, and a total of 19 critical barriers are revealed and categorised into 3 dimensions: 7 technological barriers; 6 organisational barriers; and 6 environmental barriers. The TOWS matrix is then used to formulate possible strategies for the case company to exploit the opportunities and address the barriers to the adoption of blockchain-based games. As a result, a total of 7 SO, 12 ST, 5 WO, and 1 WT strategies are proposed. Based on the PNs and the interview with experts, a roadmap including short-, medium-, and long-term action plans is also developed to facilitate the adoption of blockchain-based games

Assembly line balancing with cobots: An extensive review and critiques

Industry 4.0 encourages industries to digitise the manufacturing system to facilitate human-robot collaboration (HRC) to foster efficiency, agility and resilience. This cutting-edge technology strikes a balance between fully automated and manual operations to maximise the benefits of both humans and assistant robots (known as cobots) working together on complicated and prone-to-hazardous tasks in a collaborative manner in an assembly system. However, the introduction of HRC poses a significant challenge for assembly line balancing since, besides typical assigning tasks to workstations, the other two important decisions must also be made regarding equipping workstations with appropriate cobots as well as scheduling collaborative tasks for workers and cobots. In this article, the cobot assembly line balancing problem (CoALBP), which just initially emerged a few years ago, is thoroughly reviewed. The 4M1E (i.e., man, machine, material, method and environment) framework is applied for categorising the problem to make the review process more effective. All of the articles reviewed are compared, and their key distinct features are summarised. Finally, guidelines for additional studies on the CoALBP are offered

Real-Time Induction Motor Health Index Prediction in A Petrochemical Plant using Machine Learning

This paper presents real-time health prediction of induction motors (IMs) utilised in a petrochemical plant through the application of intelligent sensors and machine learning (ML) models. At present, maintenance engineers of the company implement time-based and condition-based maintenance techniques in periodically examining and diagnosing the health of IMs which results in sporadic breakdowns of IMs. Such breakdowns sometimes force the entire production process to stop for emergency maintenance resulting in a huge loss in the company’s revenue. Hence, top management decides to switch the operational practice to real-time predictive maintenance instead. Intelligent sensors are installed on IMs to collect necessary information related to their working statuses. ML exploits the real-time information received from intelligent sensors to flag abnormalities of mechanical or electrical components of IMs before potential failures are reached. Four ML models are investigated to evaluate which one is the best, i.e. Artificial Neural Network (ANN), Particle Swarm Optimization (PSO), Gradient Boosting Tree (GBT) and Random Forest (RF). Standard performance metrics are used to compare the relative effectiveness among different ML models including Precision, Recall, Accuracy, F1-score, and AUC-ROC curve. The results reveal that PSO not only obtains the highest average weighted Accuracy but also can differentiate the statuses (Class 0 – Class 3) of the IM more correctly than other counterpart models

An Integration of Project Management Body of Knowledge and Project Management Information System to Improve On-time Deliverable of Liquefied Natural Gas Station Construction Projects

The objective of this study is to improve the liquefied natural gas station construction project to achieve on-time delivery. Diverse tools and techniques are integrated to make various interrelated activities in the project occur effectively as planned with less cost, suggested by the Project Management Body of Knowledge (PMBOK) guideline and the Project Management Information System (PMIS). To implement the PMIS along with the PMBOK, the project management software and Internet of Things (IoT) are utilized for real-time long-distance monitoring and control of the project. The proposed approach is implemented at a real demonstration project. The results reveal that the proposed approach is quite effective, which help increase the number of projects completed on schedule from 75% in the last year to 100% this year. Moreover, the implementation of the PMIS also results in substantial reductions in the employment allowance for routine site inspections and the travel expense for round-trip vehicles travelling from the company to the site