Real-life Industrial Environment Research Articles

“Digital literacy”: Shaping industry 4.0 engineering curriculums via factory pilot-demonstrators

This work describes a joint initiative between PSG-College of technology (Coimbatore, India) and Newcastle University (UK) for the mapping, design, evaluation and roll out of technically rich ‘Digital Manufacturing’ curriculum which has been embraced with a two-fold objective: 1) to prepare final-year Engineering students for real-life industrial environments and 2) to promote the use of digital technologies across manufacturing-intensive Micro, Small and Medium Enterprises (MSMEs) that can directly benefit from their application at an engineering, managerial and shop-floor practical levels. The project started by considering both countries' national strategies for Industry 4.0 (MAKE-in India and Made Smarter, UK) to identify those areas marked as strategically critical and mapping them onto existing engineering curriculums across undergraduate engineering degrees.Based on local industry partners with clearly defined ‘digitalization’ opportunities, four industrial case studies were selected and reproduced inside both University labs in the form of student projects that were made available to all final year mechanical engineering students at both institutions. The resulting pilot projects exhibited the potential to expose undergraduate students to engineering concepts and techniques not currently covered in the taught curriculums, while offering industry a ‘soft landing’ on the use of Industry 4.0 tools which have not yet been embraced, mainly due to the lack of qualified personnel or access to specific technology skillsets, such as 3D printing, Augmented Reality and Digital Twins.

Ranking of Eco-Conscious Manufacturing Using Multi-Objective by Ratio Analysis Method

Decision-makers in the manufacturing environment struggle with challenge weighing several and choosing one based on options and criteria that clash. In the Priority Ranking System Method for Enrichment Assessments, several criteria are used to make the decision technique, in this research comprehend resolve this significant challenge. The method is enhanced in the current study by its integration with fuzzy logic and the analytic hierarchy process. The methods covered in this paper are particularly helpful for making decisions in a variety of real-life industrial environment scenarios. Wheel wear, tactile force, grinding temperature, surface roughness, recycling, toxic harm ratio, environmental pollution trend, and stability are all represented by the letters WW, TF, GT, SR, and S. WW is more crucial to the milling process than TF. WW, wheel wear; TF, tactile force; GT, grinding temperature; SR, surface roughness; R, recycling; TH, toxic harm ratio; EP, environmental pollution trend; S, stability. WW is more crucial to the milling process than TF. Lessening R is less crucial than reducing SR. To cut machining costs, care should be taken to lower the value of GT. Therefore, WW over TF, and TF over WW. WW is moderately significant over GT. Therefore, WW is assigned a relative importance value over GT, and EP is assigned a relative importance value over. Multi-objective by ratio analysis (MOORA) we choose MOORA above other multiple standards decision-making (MCDM) techniques for three main reasons. First, MOORA refers to a brand-new MCTM technique that was developed in light of the weaknesses of more traditional approaches. Therefore, we believed it should be entirely useful. The second reason, which is supported by the MCDM literature, is the computing time MOORA needs to solve the problem. Last but not least, MOORA requires little to no setup because its character is fixed and the literature recommends it should. The MOORA device is a decision-support tool for picking college students who get scholarships to boost academic success. MOORA is a selection assistance tool that the university has created to aid in decision-making. From the result it is seen that Cutting fluid 3 is showing the highest value for cutting fluid 4 is showing the lowest value. resulting in cutting fluid 3 ranked first, there cutting fluid 4 has low rank.

A Social Spider Optimization Algorithm for Hybrid Flow Shop Scheduling with Multiprocessor Task

Hybrid flow shop scheduling with multiprocessor task (HFSPMT) is a strongly NP-hard problem that has a wide range of applications in several real-life industrial environments. Due to its essential complexity and practical relevance, HFSPMT has been of an increasing interest for researchers and industrialists in the last two decades. Social spider optimization (SSO) is a recent swarm intelligence algorithm that has been rarely applied on combinatorial optimization problems. In order to make a small step toward having an idea about its effectiveness in solving combinatorial optimization, in this work, a new SSO algorithm is proposed to solve HFSPMT problem with the objective of makespan minimization. The proposed algorithm is experimented on benchmark instances and compared with other existing swarm intelligence algorithms in the literature. The obtained results and the comparisons show that the performance of the proposed algorithm is highly competitive in terms of solution quality.

Application of compressed air in the online monitoring of surface roughness and grinding wheel wear when grinding Ti-6Al-4V titanium alloy

This work aimed to improve the surface quality and precision in machining process and speed up intelligent production. Hence, this work proposed a grinding process from a control perspective which provides a cognitive decision-making process. From this viewpoint, a new approach to measure the amount of grinding wheel wear and predict the surface roughness was designed by the authors on the basis of the compressed air measuring head and hybrid algorithms between fuzzy neural networks (i.e., ANFIS)—Gaussian regression function (i.e., GPR) and Taguchi empirical analysis. A series of experiments was conducted under different processing conditions. Results showed that the proposed method can measure the abrasive wear and predict the surface roughness accurately during Ti-6Al-4V titanium alloy grinding. The proposed model can predict surface roughness values with an error rate of 0.31% and a confidence interval of 98%. This study laid the foundation for monitoring the grinding wheel wear and the surface roughness in real-life industrial environments.

Distribution planning of bulk lubricants at BP Turkey

We address the distribution planning problem of bulk lubricants at BP Turkey. The problem involves the distribution of different lube products from a single production plant to industrial customers using a heterogeneous fleet. The fleet consists of tank trucks where each tank can only be assigned to a single lube. The objective is to minimize total transportation related costs. The problem basically consists of assigning customer orders to the tanks of the trucks and determining the routes of the tank trucks simultaneously. We model this problem as a 0–1 mixed integer linear program. Since the model is intractable for real-life industrial environment we propose two heuristic approaches and investigate their performances. The first approach is a linear programming relaxation-based algorithm while the second is a rolling-horizon threshold heuristic. We propose two variants of the latter heuristic: the first uses a distance priority whereas the second has a due date priority. Our numerical analysis using company data shows that both variants of the rolling horizon threshold heuristic are able to provide good results fast.

Heuristics for a dynamic rural postman problem

This paper presents a very special cutting path determination problem appearing in a high precision tools factory, and provides two new heuristics for its resolution. Particular features of both the cutting process, and of the material to be cut, bring in a set of unusual constraints, when compared with other cutting processes, which confer additional complexity and originality to the problem. In particular, this is a matter of practical and economic relevance, since the solution methods are intended to be implemented in a real-life industrial environment. The concept of dynamic graph is exploited to deal with the arc routing problem under study, which is modelled as a dynamic rural postman problem. The constructive heuristics developed, the “higher up vertex heuristic” (HUV) and the “minimum empty path heuristic” (MEP) are tested with real data sets.

Improving productivity by using strategic inventories: Theoretical issues and field results

The study investigated the effectiveness of a new proposed inventory control technique to improve materials productivity for make-to-order and/or assembly-to-order companies. This new model is designed to manage peaks of finished products market demand, allowing the operative working capital to be reduced. The model fits real-life manufacturing environments where a satisfactory level of return on investments in capital goods is a prerequisite. Furthermore, the model can face the changing external environment and the parameters upon which production system performances depend. This is particularly true when the control technique is required to react to a reduction of the delivery lead-time, which is commonplace of the majority of competitive markets. Finally, a multistage production system environment is analysed early and the applicability of the model in various real-life industrial environments is suggested. To this purpose, a set of case histories of Italian companies belonging to different branches of industry is reported.