scholarly journals Setting optimal production lot sizes and planned lead times in a job shop

2015 ◽  
Vol 54 (20) ◽  
pp. 6105-6120 ◽  
Author(s):  
Rong Yuan ◽  
Stephen C. Graves
Keyword(s):  
Job Shop ◽  
Lead Times ◽  
Optimal Production ◽  
Lot Sizes

Constrained Optimal Production Lot Sizes for Several Products

1990 ◽  
Vol 10 (3-4) ◽  
pp. 199-228
Author(s):  
R. R. Vemuganti ◽  
David Dianich ◽  
Marilyn Oblak ◽  
H. Dabbaghi
Keyword(s):  
Optimal Production ◽  
Lot Sizes

scholarly journals LEAD-TIME, INVENTORY, AND SAFETY STOCK CALCULATION IN JOB-SHOP MANUFACTURING

2018 ◽  
Vol 58 (6) ◽  
pp. 395-401 ◽  
Author(s):  
Miguel Afonso Sellitto
Keyword(s):  
Lead Time ◽  
Job Shop ◽  
Lead Times ◽  
Lot Size ◽  
Safety Stock ◽  
Safety Stocks ◽  
Body Of Knowledge ◽  
Manufacturing Management ◽  
Workload Control ◽  
Control Body

The purpose of this article is to present a method for calculating the lead-time, the inventory, and the safety stock or buffer in job shop manufacturing, which are essentially stochastic variables. The research method is quantitative modelling. The theoretical foundation of the method relies on the techniques belonging to the WLC (workload control) body of knowledge on the manufacturing management. The study includes an application of the method in a manufacturing plant of the furniture industry, whose operation strategy requires high dependability. The company operates in a supply chain and must have high a reliability in deliveries. Adequate safety stocks, lead times, and inventory levels provide the protection against the lack of reliability in the deliveries. The inventory should remain within a certain range, being as small as possible to maintain low lead times, but not too small that it could provoke a starvation, configuring an optimization problem. The study offers guidelines for a complete application in industries. Further research shall include the influence of the variability of the lot size in the stochastic variables.

scholarly journals A Critical Analysis of Job Shop Scheduling in Context of Industry 4.0

2021 ◽  
Vol 13 (14) ◽  
pp. 7684
Author(s):  
Raja Awais Liaqait ◽  
Shermeen Hamid ◽  
Salman Sagheer Warsi ◽  
Azfar Khalid
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Intelligent Manufacturing ◽  
Distributed Scheduling ◽  
Lead Times ◽  
Shop Scheduling ◽  
Third Phase ◽  
Customized Production

Scheduling plays a pivotal role in the competitiveness of a job shop facility. The traditional job shop scheduling problem (JSSP) is centralized or semi-distributed. With the advent of Industry 4.0, there has been a paradigm shift in the manufacturing industry from traditional scheduling to smart distributed scheduling (SDS). The implementation of Industry 4.0 results in increased flexibility, high product quality, short lead times, and customized production. Smart/intelligent manufacturing is an integral part of Industry 4.0. The intelligent manufacturing approach converts renewable and nonrenewable resources into intelligent objects capable of sensing, working, and acting in a smart environment to achieve effective scheduling. This paper aims to provide a comprehensive review of centralized and decentralized/distributed JSSP techniques in the context of the Industry 4.0 environment. Firstly, centralized JSSP models and problem-solving methods along with their advantages and limitations are discussed. Secondly, an overview of associated techniques used in the Industry 4.0 environment is presented. The third phase of this paper discusses the transition from traditional job shop scheduling to decentralized JSSP with the aid of the latest research trends in this domain. Finally, this paper highlights futuristic approaches in the JSSP research and application in light of the robustness of JSSP and the current pandemic situation.

scholarly journals Energy Efficiency Improvement through Optimal Batch Sizing in Job Shop

2020 ◽  
Vol 14 (10) ◽  
pp. 6
Author(s):  
Samira Alvandi
Keyword(s):  
Job Shop ◽  
Real Life ◽  
Point Of View ◽  
Energy Efficiency Improvement ◽  
Batch Sizing ◽  
Simulation Optimisation ◽  
Lot Sizes ◽  
State Changes ◽  
Production Plans ◽  
Job Tardiness

The increasing customization of products with greater variances and smaller lot sizes, has motivated manufacturers to adopt highly dynamic production planning. The production plans not only need to adapt to the production system state changes rapidly but also need to adopt energy reduction schemes to satisfy key sustainability performance indicators. The dilemma from industry point of view is to tackle multi-faceted problem of optimising economic and environmental performance. This research aims to overcome the multi-faceted objectives of small and medium-sized enterprises (SME’s) by providing a simulation-optimisation platform that creates the best possible production plans for optimum results. The applicability of the proposed framework is demonstrated through a real-life job-shop environment with the focus on optimisation of energy as well as job tardiness.

scholarly journals ENHANCEMENT OF PRODUCTION BY LEAN MANUFACTURING METHOD

2022 ◽  
Vol 10 (1) ◽  
pp. 01-04
Author(s):  
Vivek Vishnu ◽  
◽  
Vineet Kumar Dwivedi ◽  
Keyword(s):  
High Pressure ◽  
Lean Manufacturing ◽  
Job Shop ◽  
Lessons Learned ◽  
Lead Times ◽  
Manufacturing Method ◽  
Delivery Performance ◽  
Steel Tank ◽  
Pressure Storage ◽  
String Diagram

The thesis proposes a method for introducing lean manufacturing using string diagram in an operating CNG high pressure storage tank manufacturing job shop at Jayfe Cylinder Ltd. Haryana. By applying lean manufacturing using process layout diagram to produce part families with similar manufacturing processes and stable demand, plants expect to reduce costs and lead-times and improve quality and delivery performance. The thesis outlines a method for assessing, designing, and implementing lean manufacturing using process layout diagram, and illustrates this process with an example. A manufacturing cell that produces high pressure steel tank container for commercial & automobile customers is implemented at cylinder tank Machining Centers. The conclusion of the thesis highlights the key lessons learned from this process.

Study of lot sizes on job shop systems performance using simulation

1995 ◽  
Vol 2 (6) ◽  
pp. 277-289 ◽  
Author(s):  
G. Habchi ◽  
Ch. Labrune
Keyword(s):  
Job Shop ◽  
Lot Sizes

scholarly journals Manufacturing 4.0 Operations Scheduling with AGV Battery Management Constraints

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4948 ◽  
Author(s):  
Moussa Abderrahim ◽  
Abdelghani Bekrar ◽  
Damien Trentesaux ◽  
Nassima Aissani ◽  
Karim Bouamrane
Keyword(s):  
Industry 4.0 ◽  
Job Shop ◽  
Experimental Tests ◽  
Automated Guided Vehicles ◽  
Lead Times ◽  
Battery Management ◽  
Production Lines ◽  
Operations Scheduling ◽  
Proposed Model ◽  
Time Minimization

The industry 4.0 concepts are moving towards flexible and energy efficient factories. Major flexible production lines use battery-based automated guided vehicles (AGVs) to optimize their handling processes. However, optimal AGV battery management can significantly shorten lead times. In this paper, we address the scheduling problem in an AGV-based job-shop manufacturing facility. The considered schedule concerns three strands: jobs affecting machines, product transport tasks’ allocations and AGV fleet battery management. The proposed model supports outcomes expected from Industry 4.0 by increasing productivity through completion time minimization and optimizing energy by managing battery replenishment. Experimental tests were conducted on extended benchmark literature instances to evaluate the efficiency of the proposed approach.

Sign in / Sign up

Export Citation Format

Share Document