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Processes
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Sustainable Production Scheduling and Supply Chain Management under Resource Constraints...
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Sustainable Production Scheduling and Supply Chain Management under Resource Constraints and Factory Eligibility

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Sustainable Processes".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 16991

Special Issue Editors

Dr. Shib Sankar Sana

E-Mail Website
Guest Editor
Department of Mathematics, Kishore Bharati Bhagini Nivedita College, Kolkata, India
Interests: inventory; production planning and control; bio-mathematics; supply chain management
Special Issues, Collections and Topics in MDPI journals
Dr. Subrata Saha

E-Mail Website
Guest Editor
Department of Materials and Production, Aalborg University, 9220 Aalborg, Denmark
Interests: supply chain management; inventory control

Special Issue Information

Dear Colleagues,

In today's competitive environment, manufacturing industries are facing complex challenges such as energy consumption, pollution, production time, and operational costs. With the intensification of market competition and the general trend of economic globalization, production systems with more than one production center are becoming more and more common. For example, instead of producing all the components needed for the final product, more and more enterprises prefer to receive them from eligible suppliers and assemble them in the main factory. This outsourcing strategy in production is widely used in automobiles and electronics. Many companies such as Dell, Lucent, Cisco, and HP outsource most of their components and single-factory firms are less common, with multi-plant companies being more commonplace. Therefore, suppliers are taking on a more important role in practice to achieve lower production costs, reduced energy consumption, carbon emissions and pollution, higher product quality, and lower management risks. This type of production system, the so-called distributed manufacturing system, can reduce production costs while keeping or increasing product quality. 
Under such aforementioned conditions, production planning and control plays a vital role in achieving the ideal result. Shop floor production planning and control, which is well known as a scheduling problem and efforts to schedule jobs and assign them to processing machines so that a given criterion is optimized are essential. Concurrent-type scheduling models and solution approaches for the processing, operation and assembly stages have many applications in real-world conditions, and so are receiving increasing attention in the field of academic research and manufacturing enterprises. There are different approaches to achieve this aim depending on the problem’s features and its restrictions. A distributed flow shop scheduling problem followed by the assembly (DAFSP) shop is a generalization of the assembly flow shop scheduling problem (AFSP), which provides a closer approximation to a range of problems encountered in real manufacturing systems. A more constrained version of this problem is the distributed assembly permutation flow shop scheduling problem (DAPFSP), wherein the same sequence of parts is maintained for all machines in each factory.

This study aims to address a distributed assembly permutation flow shop scheduling problem (DAPFSP) with non-identical factories considering budget constraints. Suppose that several products of different kinds are ordered to be produced. Each product consists of a set of parts that are processed through several factories. All of these factories have a flow shop with different technology levels, and so their performance is different in terms of processing time, energy consumption, pollution, and operational costs. Moreover, we have budget constraints, so we can assign limited parts to the high-tech factories. The second stage is the assembly stage, wherein there is a work station to assemble the ready parts into the products. Many worldwide companies have needed to alter their outsourcing and manufacturing activities to deal with the supply-chain disruptions and uncertainty in demand. Many companies have implemented these new measures well in response to the disruptions through digital technology application, supply chain digitization, green supply chain operations and business model innovations. 

This Special Issue will concentration on analyzing the new practices of production and job shop scheduling logistics, supply chain management, humanitarian supply chain, and logistics production management.
We encourage and welcome high-quality applied and methodological articles on such topics as those listed below, but not limited to:

  • job shop scheduling
  • green production technology
  • production planning and scheduling with budget constrains
  • humanitarian supply chain and logistics production planning
  • big data analysis in job shop scheduling problems
  • optimum methods of operations to improve the 3Rs (responsiveness, resilience, and restoration) in supply chain
  • soft computing techniques to job scheduling under ergonomic constraints in the manufacturing industry
  • inventory control in production planning and job shop scheduling
  • hybrid flow shop scheduling problem with setup time and assembly operations
  • maintenance operations and access restrictions to machines
  • multi-objective scheduling problems
  • JIT scheduling problem in the machine flow shop
  • leanness concept and system dynamics approach in manufacturing systems
  • goal programming approach to optimizes sustainable operations management

Dr. Shib Sankar Sana
Dr. Subrata Saha
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (4 papers)

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Research

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13 pages, 2637 KiB  
Article
Reliability Modelling through the Three-Parametric Weibull Model Based on Microsoft Excel Facilities
by Aurel Mihail Titu, Andrei Alexandru Boroiu, Alexandru Boroiu, Mihai Dragomir, Alina Bianca Pop and Stefan Titu
Processes 2022, 10(8), 1585; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10081585 - 12 Aug 2022
Cited by 2 | Viewed by 1367
Abstract
The paper aims to capitalize on the new features that are offered by the Microsoft Excel calculation program for reliability modeling, using the Median Ranks estimator that is calculated directly with the BETA.INV function, not estimated by various algebraic estimators, as is generally [...] Read more.
The paper aims to capitalize on the new features that are offered by the Microsoft Excel calculation program for reliability modeling, using the Median Ranks estimator that is calculated directly with the BETA.INV function, not estimated by various algebraic estimators, as is generally the case. Starting from this first step, a method of modeling reliability is elaborated through the three-parametric Weibull model that is based exclusively on this software, which is accessible to anyone and can be used even in the case of online learning, which is widespread in recent years due to the pandemic situation. The probability plotting method is applied, using the Median Ranks estimator that is calculated directly with the BETA.INV function for a probability equal to 0.5. A flowchart is made for the proposed method, which could be easily translated into a calculation program. By representing in logarithmic coordinates, we determined the Weibull models for different values that were initially adopted for the location parameter: using as a criterion the coefficient of determination that was obtained using the trendline function for the linear model, it was possible to identify, by successive tests, the optimal value of the location parameter—for which the three-parametric model has a good likelihood. By the proposed method, this value can be found following this iterative process. So, based on the current facilities of the Microsoft Excel program, a precise and easy-to-apply method has been achieved, through which an appropriate three-parametric Weibull model can be identified. Full article
(This article belongs to the Special Issue Sustainable Production Scheduling and Supply Chain Management under Resource Constraints and Factory Eligibility)
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18 pages, 2683 KiB  
Article
A Lean Manufacturing Progress Model and Implementation for SMEs in the Metal Products Industry
by Chien-Yi Huang, Dasheng Lee, Shu-Chuan Chen and William Tang
Processes 2022, 10(5), 835; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10050835 - 24 Apr 2022
Cited by 8 | Viewed by 8253
Abstract
The manufacturing industry faces the challenge of small and diversified customer orders. To meet this challenge, strong internal production capabilities are required. A lean manufacturing process that uses fewer resources and offers greater process improvement will help SMEs to continue to contribute to [...] Read more.
The manufacturing industry faces the challenge of small and diversified customer orders. To meet this challenge, strong internal production capabilities are required. A lean manufacturing process that uses fewer resources and offers greater process improvement will help SMEs to continue to contribute to the global economy. Though SMEs provide most employment opportunities, previous studies have focused on large companies in auto-manufacturing-related industries. With the commitment and support of the management, and the application of a value stream map (VSM) and related improvement tools, we produced a practical process improvement model for a lean manufacturing system in an SME. With the commitment and support of the management and the joint efforts of the project improvement staff, the 10 improvement projects over a six-month period all achieved their goals: reduction in lead time from 26 days to 19.5 days, improvement of welding per people per hour (PPH) efficiency by 28.3%, improvement of packaging PPH efficiency by 64.1%, improvement of working in process (WIP) efficiency at the production site by 83.84%, and improvement of raw material storage by 83.84%. The efficiency of the raw material warehouse inventory was improved by 58.63%, and the efficiency of the shipment completion rate was improved by 14.5%. Full article
(This article belongs to the Special Issue Sustainable Production Scheduling and Supply Chain Management under Resource Constraints and Factory Eligibility)
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16 pages, 312 KiB  
Article
SMEs in Automotive Supply Chains: A Survey on Six Sigma Performance Perceptions of Czech Supply Chain Members
by Marcel Rolf Pfeifer
Processes 2022, 10(4), 698; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10040698 - 04 Apr 2022
Cited by 3 | Viewed by 1962
Abstract
Six sigma is understood as a technique for the continuous improvement in process quality; however, it has been rarely scientifically analysed in small- and medium-sized enterprises (SMEs). SMEs representthe vast majority of enterprises throughout economies and contribute to automotive supply chains in various [...] Read more.
Six sigma is understood as a technique for the continuous improvement in process quality; however, it has been rarely scientifically analysed in small- and medium-sized enterprises (SMEs). SMEs representthe vast majority of enterprises throughout economies and contribute to automotive supply chains in various tier ranks. As SMEs are known to lack resources and skills while focusing on short-term benefits rather than on long-term gradual improvements, the aim of of this paper is to analyse the perception of six sigma process capabilities in automotive supply chains assuming differences in company size, supply chain rank and six sigma duration. This was tested with Fisher’s exact test. Companies with less than 1000 employees, subsuppliers and companies with a six sigma implementation in the last 3 years struggled to meet six sigma principles, suggesting that mainly small companies inhibit a risk for the supply chain. These findings contribute to the existing theoretical body of knowledge by identifying a three-to-five-year period for six sigma implementations until six sigma maturity. Practically, the findings contribute to the research by explaining the need for a continuous supplier development over a three-to-five-year period until the company meets its performance requirements, with a supply chain risk incorporated in lower-tier ranks and with small companies. Full article
(This article belongs to the Special Issue Sustainable Production Scheduling and Supply Chain Management under Resource Constraints and Factory Eligibility)

Review

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31 pages, 2790 KiB  
Review
Food Quality, Drug Safety, and Increasing Public Health Measures in Supply Chain Management
by Mona Haji, Laoucine Kerbache and Tareq Al-Ansari
Processes 2022, 10(9), 1715; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10091715 - 28 Aug 2022
Cited by 7 | Viewed by 4353
Abstract
Over the last decade, there has been an increased interest in public health measures concerning food quality and drug safety in supply chains and logistics operations. Against this backdrop, this study systematically reviewed the extant literature to identify gaps in studying food quality [...] Read more.
Over the last decade, there has been an increased interest in public health measures concerning food quality and drug safety in supply chains and logistics operations. Against this backdrop, this study systematically reviewed the extant literature to identify gaps in studying food quality and drug safety, the proposed solutions to these issues, and potential future research directions. This study utilized content analysis. The objectives of the review were to (1) identify the factors affecting food quality and possible solutions to improve results, (2) analyze the factors that affect drug safety and identify ways to mitigate them through proper management; and (3) establish integrated supply chains for food and drugs by implementing modern technologies, followed by one another to ensure a multi-layered cross-verification cascade and resource management at the different phases to ensure quality, safety, and sustainability for the benefit of public health. This review investigated and identified the most recent trends and technologies used for successfully integrated supply chains that can guarantee food quality and drug safety. Using appropriate keywords, 298 articles were identified, and 205 were shortlisted for the analysis. All analysis and conclusions are based on the available literature. The outcomes of this paper identify new research directions in public health and supply chain management. Full article
(This article belongs to the Special Issue Sustainable Production Scheduling and Supply Chain Management under Resource Constraints and Factory Eligibility)
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