Using MACBETH method for supplier selection in manufacturing environment

Supplier selection is always found to be a complex decision-making problem in manufacturing environment. The presence of several independent and conflicting evaluation criteria, either qualitative or quantitative, makes the supplier selection problem a candidate to be solved by multi-criteria decision-making (MCDM) methods. Even several MCDM methods have already been proposed for solving the supplier selection problems, the need for an efficient method that can deal with qualitative judgments related to supplier selection still persists. In this paper, the applicability and usefulness of measuring attractiveness by a categorical-based evaluation technique (MACBETH) is demonstrated to act as a decision support tool while solving two real time supplier selection problems having qualitative performance measures. The ability of MACBETH method to quantify the qualitative performance measures helps to provide a numerical judgment scale for ranking the alternative suppliers and selecting the best one. The results obtained from MACBETH method exactly corroborate with those derived by the past researchers employing different mathematical approaches

Hybrid genetic algorithm to minimize scheduling cost with unequal and job dependent earliness tardiness cost

[EN] This article presents two combinatorial genetic algorithms (GA), unequal earliness tardiness-GA (UET-GA) and job-dependent earliness tardiness-GA (JDET-GA) for the single-machine scheduling problem to minimize earliness tardiness (ET) cost. The sequence of jobs produced in basic UET and JDET as a chromosome is added to the random population of GA. The best sequence from each epoch is also injected as a population member in the subsequent epoch. The proposed improvement seeks to achieve convergence in less time to search for an optimal solution. Although the GA has been implemented very successfully on many different types of optimization problems, it has been learnt that the algorithm has a search ability difficulty that makes computations NP-hard for types of optimization problems, such as permutation-based optimization problems. The use of a plain random population initialization results in this flaw. To reinforce the random population initialization, the proposed enhancement is utilized to obtain convergence and find a promising solution. The cost is further significantly lowered offering the due date as a decision variable with JDET-GA. Multiple tests were run on well-known single-machine benchmark examples to demonstrate the efficacy of the proposed methodology, and the results are displayed by comparing them with the fundamental UET and JDET approaches with a notable improvement in cost reduction.Bari, P.; Karande, P.; Bag, V. (2024). Hybrid genetic algorithm to minimize scheduling cost with unequal and job dependent earliness tardiness cost. International Journal of Production Management and Engineering. 12(1):19-30. https://doi.org/10.4995/ijpme.2024.19277193012

Cost Factor Focused Scheduling and Sequencing: A Neoteric Literature Review

The hastily emergent concern from researchers in the application of scheduling and sequencing has urged the necessity for analysis of the latest research growth to construct a new outline. This paper focuses on the literature on cost minimization as a primary aim in scheduling problems represented with less significance as a whole in the past literature reviews. The purpose of this paper is to have an intensive study to clarify the development of cost-based scheduling and sequencing (CSS) by reviewing the work published over several parameters for improving the understanding in this field. Various parameters, such as scheduling models, algorithms, industries, journals, publishers, publication year, authors, countries, constraints, objectives, uncertainties, computational time, and programming languages and optimization software packages are considered. In this research, the literature review of CSS is done for thirteen years (2010-2022). Although CSS research originated in manufacturing, it has been observed that CSS research publications also addressed case studies based on health, transportation, railway, airport, steel, textile, education, ship, petrochemical, inspection, and construction projects. A detailed evaluation of the literature is followed by significant information found in the study, literature analysis, gaps identification, constraints of work done, and opportunities in future research for the researchers and experts from the industries in CSS

Neurodevelopmental disorders in children aged 2-9 years: Population-based burden estimates across five regions in India.

BACKGROUND: Neurodevelopmental disorders (NDDs) compromise the development and attainment of full social and economic potential at individual, family, community, and country levels. Paucity of data on NDDs slows down policy and programmatic action in most developing countries despite perceived high burden. METHODS AND FINDINGS: We assessed 3,964 children (with almost equal number of boys and girls distributed in 2-<6 and 6-9 year age categories) identified from five geographically diverse populations in India using cluster sampling technique (probability proportionate to population size). These were from the North-Central, i.e., Palwal (N = 998; all rural, 16.4% non-Hindu, 25.3% from scheduled caste/tribe [SC-ST] [these are considered underserved communities who are eligible for affirmative action]); North, i.e., Kangra (N = 997; 91.6% rural, 3.7% non-Hindu, 25.3% SC-ST); East, i.e., Dhenkanal (N = 981; 89.8% rural, 1.2% non-Hindu, 38.0% SC-ST); South, i.e., Hyderabad (N = 495; all urban, 25.7% non-Hindu, 27.3% SC-ST) and West, i.e., North Goa (N = 493; 68.0% rural, 11.4% non-Hindu, 18.5% SC-ST). All children were assessed for vision impairment (VI), epilepsy (Epi), neuromotor impairments including cerebral palsy (NMI-CP), hearing impairment (HI), speech and language disorders, autism spectrum disorders (ASDs), and intellectual disability (ID). Furthermore, 6-9-year-old children were also assessed for attention deficit hyperactivity disorder (ADHD) and learning disorders (LDs). We standardized sample characteristics as per Census of India 2011 to arrive at district level and all-sites-pooled estimates. Site-specific prevalence of any of seven NDDs in 2-<6 year olds ranged from 2.9% (95% CI 1.6-5.5) to 18.7% (95% CI 14.7-23.6), and for any of nine NDDs in the 6-9-year-old children, from 6.5% (95% CI 4.6-9.1) to 18.5% (95% CI 15.3-22.3). Two or more NDDs were present in 0.4% (95% CI 0.1-1.7) to 4.3% (95% CI 2.2-8.2) in the younger age category and 0.7% (95% CI 0.2-2.0) to 5.3% (95% CI 3.3-8.2) in the older age category. All-site-pooled estimates for NDDs were 9.2% (95% CI 7.5-11.2) and 13.6% (95% CI 11.3-16.2) in children of 2-<6 and 6-9 year age categories, respectively, without significant difference according to gender, rural/urban residence, or religion; almost one-fifth of these children had more than one NDD. The pooled estimates for prevalence increased by up to three percentage points when these were adjusted for national rates of stunting or low birth weight (LBW). HI, ID, speech and language disorders, Epi, and LDs were the common NDDs across sites. Upon risk modelling, noninstitutional delivery, history of perinatal asphyxia, neonatal illness, postnatal neurological/brain infections, stunting, LBW/prematurity, and older age category (6-9 year) were significantly associated with NDDs. The study sample was underrepresentative of stunting and LBW and had a 15.6% refusal. These factors could be contributing to underestimation of the true NDD burden in our population. CONCLUSIONS: The study identifies NDDs in children aged 2-9 years as a significant public health burden for India. HI was higher than and ASD prevalence comparable to the published global literature. Most risk factors of NDDs were modifiable and amenable to public health interventions

A Fuzzy-MOORA approach for ERP system selection

In today’s global and dynamic business environment, manufacturing organizations face the tremendous challenge of expanding markets and meeting the customer expectations. It compels them to lower total cost in the entire supply chain, shorten throughput time, reduce inventory, expand product choice, provide more reliable delivery dates and better customer service, improve quality, and efficiently coordinate demand, supply and production. In order to accomplish these objectives, the manufacturing organizations are turning to enterprise resource planning (ERP) system, which is an enterprise-wide information system to interlace all the necessary business functions, such as product planning, purchasing, inventory control, sales, financial and human resources into a single system having a shared database. Thus to survive in the global competitive environment, implementation of a suitable ERP system is mandatory. However, selecting a wrong ERP system may adversely affect the manufacturing organization’s overall performance. Due to limitations in available resources, complexity of ERP systems and diversity of alternatives, it is often difficult for a manufacturing organization to select and install the most suitable ERP system. In this paper, two ERP system selection problems are solved using fuzzy multi-objective optimization on the basis of ratio analysis (MOORA) method and it is observed that in both the cases, SAP is the best solution

A Facility Layout Selection Model using MACBETH Method

Abstract Facility layout selection is a multi-criteria decision-making (MCDM) problem which primarily involves in evaluating multiple candidate layouts, designed according to a set of common criteria for choosing the best one. Designing multiple facility layouts is an easy task, thank to availability of different facility layout design software. However, the decision of selecting the best layout becomes complex due to the involvement of several conflicting evaluation criteria. Thus, the decision makers often face the problem of selecting the best one from the available facility layout alternatives. In this paper, the application of Measuring Attractiveness by a Categorical Based Evaluation TecHnique (MACBETH) approach is demonstrated while solving two real time facility layout selection problems. Even though MACBETH approach is recognized as an efficient MCDM tool for qualitative performance measures, it is also capable to deal with quantitative performance measures, as demonstrated in this paper. For the first example, having qualitative and quantitative data, the results obtained from MACBETH method exactly corroborate with those derived by the past researchers. In the second example, MACBETH method is applied to find out the best facility layout for a newly fangled case

Application of PROMETHEE-GAIA method for non-traditional machining processes selection

With ever increasing demand for manufactured products of hard alloys and metals with high surface finish and complex shape geometry, more interest is now being paid to non-traditional machining (NTM) processes, where energy in its direct form is used to remove material from workpiece surface. Compared to conventional machining processes, NTM processes possess almost unlimited capabilities and there is a strong believe that use of NTM processes would go on increasing in diverse range of applications. Presence of a large number of NTM processes along with complex characteristics and capabilities, and lack of experts in NTM process selection domain compel for development of a structured approach for NTM process selection for a given machining application. Past researchers have already attempted to solve NTM process selection problems using various complex mathematical approaches which often require a profound knowledge in mathematics/artificial intelligence from the part of process engineers. In this paper, four NTM process selection problems are solved using an integrated PROMETHEE (preference ranking organization method for enrichment evaluation) and GAIA (geometrical analysis for interactive aid) method which would act as a visual decision aid to the process engineers. The observed results are quite satisfactory and exactly match with the expected solutions

The m-polar fuzzy ELECTRE-I integrated AHP approach for selection of non-traditional machining processes

AbstractIn the literature, there are a number of decision-making strategies that can be used to choose the best NTM processes. Chen (2014) introduced a novel method to handle fuzzy data that includes multipolar uncertainty, referred to as the m-polar fuzzy set (mFS) approach. The mFS method, along with other multi-criteria decision-making (MCDM) techniques, is a good way to choose between options. An illustration of such a combination is the mFS elimination and choice translating reality-I (ELECTRE-I) . A criteria weight approach is also needed to increase the accuracy of the mFS ELECTRE-I method. The mFS ELECTRE-I method and the analytical hierarchy process (AHP) criteria weight calculation method are combined in the current work. The unique thing about this method is that it can be used to solve both MCDM and MCGDM problems by combining the mFS ELECTRE-I with the AHP criteria weight method. A single-dimensional weight sensitivity analysis is performed to confirm the technique’s stability for different criterion weights for the AHP method on alternative rank performance. The results of the NTM process selection are validated by previous research findings. EDM turned out to be the best way to create machine precise holes on duralumin alloy, and ECM turned out to be the best alternative to generate the surface of revolution in stainless steel. A C++-based soft solution that uses the mFS ELECTRE-I technique to analyze various MCDM and MCGDM problems has been developed. With the soft solution, you can fix problems with selecting the FMS, the robot, and so on