“Technological intelligence” is the capacity to appreciate and adapt technological advancements, and “artificial intelligence” is the key to achieve persuasive operational transformations in majority of contemporary organizational set-ups. Implicitly, artificial intelligence (the philosophies of machines to think, behave and perform either same or similar to humans) has knocked the doors of business organizations as an imperative activity. Artificial intelligence, as a discipline, initiated by scientist John McCarthy and formally publicized at Dartmouth Conference in 1956, now occupies a central stage for many organizations. Implementation of artificial intelligence provides competitive edge to an organization with a definite augmentation in its social and corporate status. Mere application of a concept will not furnish real output until and unless its performance is reviewed systematically. Technological changes are dynamic and advancing at a rapid rate. Subsequently, it becomes highly crucial to understand that where have the people reached with respect to artificial intelligence research. The present article aims to review significant work by eminent researchers towards artificial intelligence in the form of top contributing universities, authors, keywords, funding sources, journals and citation statistics.,As rightly remarked by past researchers that reviewing is learning from experience, research team has reviewed (by applying systematic literature review through bibliometric analysis) the concept of artificial intelligence in this article. A sum of 1,854 articles extracted from Scopus database for the year 2018–2019 (31st of May) with selected keywords (artificial intelligence, genetic algorithms, agent-based systems, expert systems, big data analytics and operations management) along with certain filters (subject–business, management and accounting; language-English; document–article, article in press, review articles and source-journals).,Results obtained from cluster analysis focus on predominant themes for present as well as future researchers in the area of artificial intelligence. Emerged clusters include Cluster 1: Artificial Intelligence and Optimization; Cluster 2: Industrial Engineering/Research and Automation; Cluster 3: Operational Performance and Machine Learning; Cluster 4: Sustainable Supply Chains and Sustainable Development; Cluster 5: Technology Adoption and Green Supply Chain Management and Cluster 6: Internet of Things and Reverse Logistics.,The result of review of selected studies is in itself a unique contribution and a food for thought for operations managers and policy makers.

Role of artificial intelligence in operations environment: a review and bibliometric analysis

There is a tremendous increase in the demand for converting biomaterials into high-quality industrially manufactured human body parts, also known as medical implants. Drug delivery systems, bone plates, screws, cranial, and dental devices are the popular examples of these implants - the potential alternatives for human life survival. However, the processing techniques of an engineered implant largely determine its preciseness, surface characteristics, and interactive ability with the adjacent tissue(s) in a particular biological environment. Moreover, the high cost-effective manufacturing of an implant under tight tolerances remains a challenge. In this regard, several subtractive or additive manufacturing techniques are employed to manufacture patient-specific implants, depending primarily on the required biocompatibility, bioactivity, surface integrity, and fatigue strength. The present paper reviews numerous non-degradable and degradable metallic implant biomaterials such as stainless steel (SS), titanium (Ti)-based, cobalt (Co)-based, nickel-titanium (NiTi), and magnesium (Mg)-based alloys, followed by their processing via traditional turning, drilling, and milling including the high-speed multi-axis CNC machining, and non-traditional abrasive water jet machining (AWJM), laser beam machining (LBM), ultrasonic machining (USM), and electric discharge machining (EDM) types of subtractive manufacturing techniques. However, the review further funnels down its primary focus on Mg, NiTi, and Ti-based alloys on the basis of the increasing trend of their implant applications in the last decade due to some of their outstanding properties. In the recent years, the incorporation of cryogenic coolant-assisted traditional subtraction of biomaterials has gained researchers' attention due to its sustainability, environment-friendly nature, performance, and superior biocompatible and functional outcomes fitting for medical applications. However, some of the latest studies reported that the medical implant manufacturing requirements could be more remarkably met using the non-traditional subtractive manufacturing approaches. Altogether, cryogenic machining among the traditional routes and EDM among the non-traditional means along with their variants, were identified as some of the most effective subtractive manufacturing techniques for achieving the dimensionally accurate and biocompatible metallic medical implants with significantly modified surfaces. 

/pdf/a-comprehensive-review-on-metallic-implant-biomaterials-and-1jejcof2.pdf

A comprehensive review on metallic implant biomaterials and their subtractive manufacturing

Defects are considered as one of the wastes in manufacturing systems that negatively affect the delivery times, cost and quality of products leading to manufacturing companies facing a critical situation with the customers and to not comply with the IPC-A-610E standard for the acceptability of electronic components. This is the case is a manufacturing company located in Tijuana, Mexico. Due to an increasing demand on the products manufactured by this company, several defects have been detected in the welding process of electronic boards, as well as in the components named Thru-Holes. It is for this reason that this paper presents a lean manufacturing application case study. The objective of this research is to reduce at least 20% the defects that are generated during the welding process. In addition, it is intended to increase 20% the capacity of three double production lines where electronic boards are processed. As method, the Plan-Do-Check-Act (PDCA) cycle, is applied. The Pareto charts and the flowchart are used as support tools. As results, defects decreased 65%, 79%, and 77% in three analyzed product models. As conclusion, the PDCA cycle, the Pareto charts, and the flowchart are excellent quality tools that help to decrease the number of defective components.

Applying the Plan-Do-Check-Act (PDCA) cycle to reduce the defects in the manufacturing industry. A case study

Purpose: The present study aims to assess the role of supply chain resilience as an operational excellence approach to deal with disruptions caused by coronavirus pandemic in the food supply chain of an agri-food supply firm. Design/methodology/approach: The case study method was used to analyse the disruptions faced by the agricultural food supply chain during the pandemic. The study applies a dynamic capability theory as a foundation to develop a contextualised resilience framework for agri-food supply chain to achieve operational excellence. The case has been analysed by using situation-actor-process (SAP) and learning-action-performance (LAP) framework. Findings: The SAP aspect of framework points that the flexibility amongst actors for a resilient agriculture supply chain worsened due to the lockdown measures post COVID-19. The LAP aspect of framework suggests how resilience can be built at the supply, demand and logistics end through various proactive and reactive practices such as collaboration, coordination, ICT and ground-level inputs. Lack of commitment and inadequate support from top management towards supply chain resilience are also observed as significant challenges to maintain operational excellence during the pandemic. Research limitations/implications: One of the major implications of the study is that a mix of capabilities rather than a single capability can be the most appropriate way for making the supply chain resilient to maintain operational excellence during the pandemic. However, the sources of disruptions need to be duly recognised to derive the best-contextualised resilience framework for agri-food supply chains. Originality/value: The development of a contextualised research framework as well as research propositions for analysing supply chain resilience are the major contribution of this study. © 2021, Emerald Publishing Limited.

/pdf/impact-of-disruptions-in-agri-food-supply-chain-due-to-covid-4oon4r0bau.pdf

Impact of disruptions in agri-food supply chain due to COVID-19 pandemic: contextualised resilience framework to achieve operational excellence

The purpose of this paper is to review the existing literature on the critical success factors (CSFs) of various continuous improvement (CI) like total quality management (TQM), Lean, Six Sigma and Lean Six Sigma (LSS), and perform a content analysis (CA) leading to an agenda for future research.,CA is based on literature review of 41 papers published in peer-reviewed scholarly journals. A four-stage methodology is used by the authors, with Stage 1 featuring relevant material collection; Stage 2 presenting a descriptive analysis; Stage 3 outlining the category selection; and Stage 4 featuring the material evaluation using clustering and Pareto analysis.,The CA revealed various research implications and directions for the future. The number of studies in the literature regarding CSF assessment is found to be far from substantial while compared to CI implementation. Assessment methodologies developed have been ranging from qualitative to quantitative models. Key gaps were identified and directions for CSF assessment are proposed which requires further validation.,Only articles that appeared in peer-reviewed journals were analyzed; conference papers, reports, manuals and white papers from practice were excluded. Another limitation of the paper would be the scope of CA limited to four CI constructs – TQM, Lean, Six Sigma and LSS. Research implications indicate that the future studies in this domain would be intensive toward analyzing the vital CSFs for enterprise organizational excellence and not merely process excellence.,This review study can serve as a resource for both researchers and practitioners to understand the importance of CSFs and positioning CSFs for the successful implementation of CI programs.,The CA on the existing literature on CSFs for CI presents a unique, systematic effort to identify an agenda for future research. This study is the apparently the first of its kind on CSF assessment.

Critical success factors of TQM, Six Sigma, Lean and Lean Six Sigma: A literature review and key findings

Defective parts in manufacturing is a serious issue faced by every manufacturer. Even after proper care in design, material selection and manufacturing of product, there exists a defective part. The purpose of this paper is to explore the quality of the manufacturing, and find the use of effective quality tools to reduce the part defect rate in an electrical parts manufacturing unit, thereby, reducing the replaced cost of defective parts.,With the help of quality initiatives, like total quality management (TQM) and Lean Six Sigma (LSS), the firms can produce quality product in each stage of production. The paper focuses on the primary data collected from the XYZ electric manufacturer.,The main finding of this case analysis is that by the effective use of quality tools, the defective part return rate can be reduced, because of which the firm can observe reduction in replaced cost of almost INR24 lakh. In addition, 10A switch part contributes more in replacement cost. Further, it adds to the 35 percent of the overall part rejection.,The study is more focused on particular type of switch product and can extend to other types of products. In addition, the analysis reveals the results of only 88 percent of the defective products.,The study provides results of the improved quality by effective use of quality tools and discusses the different types of defects in the electrical parts manufacturing. Introducing TQM and LSS to manufacturing can reduce the customer return rate to 1,300 parts per million (PPM) and even to 1,000 PPM in future.,The paper discusses the quality issues in the electrical manufacturer. Moreover, the case analysis briefs effective ways to improve the product quality and reduce the rejection rate.

Defect reduction in an electrical parts manufacturer: a case study

This study aims to utilize DMAIC methodology along with value stream mapping and other Lean Six Sigma tools in a major automobile light manufacturing industry to reduce defect rates and increase production capacity in their manufacturing line. The study also proposes a modified framework based on lean principles and FlexSim to identify and reduce waste in the selected industry.,A Lean Six Sigma modified framework has been deployed with DMAIC to reduce the defect rate and increase the production rate. Various tools like value stream mapping, brainstorming, Pareto charts, 5S, kanban, etc. have been used at different phases of DMAIC targeting wastes and inventory in the production line. Also, a simulation model has been utilized for the automobile light manufacturing industry to improve the machine utilization time with varying batch sizes.,The results of the study indicated a 53% reduction in defect rates. Thus, there would be an expected improvement in sigma value from 3.78 to 3.89 and a reduction in defects per million opportunities (DPMO) from 11,244 to 8,493. Additionally, simulation model using FlexSim was developed, and the optimum ordering batch size of raw material was obtained. It was also analyzed that idle time for various stations could be reduced by up to 30%.,The utilized framework helps identify defects for managers to increase production efficiency. The workers, operators and supervisors on the production line also need to be trained regularly for identifying the areas of improvement.,The modified Lean Six Sigma framework used in this study includes FlexSim simulation to make the framework robust, which has not been used with LSS tools in the literature studied. Also, the LSS finds very less application in the manufacturing domain, considering which this study tends to add value in existing literature taking a case of an automobile light manufacturing industry.

Application of Lean Six Sigma framework for improving manufacturing efficiency: a case study in Indian context

Abstract The shortcoming of conventional manufacturing (CM) is that it cannot manufacture geometrically complex parts with high repeatability and good surface properties. In order to overcome these shortcomings of CM, additive manufacturing (AM) is the major alternative to the CM. However, the usefulness and performance of parts manufactured through AM are closely correlated with dimensional accuracy and surface roughness, SR (Ra). Therefore, an investigation was carried out in this study for dimensional accuracy and surface roughness of 3D printed parts fabricated in different orientations. In the investigation, four orientation patterns are considered. The part is lying on the base (A), part is lying on the long edge (B), part is lying on the short edge (C), and the part is inclined to 45°(D) to the surface of the base plate (refer to Fig. 2). Orientations, i.e., A, B, C, and D, were explored for the variations in dimensional deviation and SR. In addition, an analysis was carried out using scanning electron microscopy (SEM) on fabricated parts. The results obtained exhibit a variation in dimensional accuracy and change in SR with different part orientations. Among all orientations, the largest surface area of the component in contact with the base plate (A) was the most suitable. 

/pdf/investigating-the-dimensional-accuracy-and-surface-roughness-2hrgj4km.pdf

Investigating the Dimensional Accuracy and Surface Roughness for 3D Printed Parts Using a Multi-jet Printer

In the present competitive scenario most of the companies are using improvement strategies like lean and Six Sigma for obtaining good quality products, reduction in overall cost and for enhancing a...

Implementation of Lean Six Sigma framework in a large scale industry: a case study

State of the art in finite element approaches for milling process: a review

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