Lot-sizing in flow-shop with energy consideration for sustainable manufacturing systems

Masmoudi, Oussama; Yalaoui, Alice; Ouazène, Yassine; Chehade, Hicham

doi:10.1016/j.ifacol.2015.06.169

Cited by 19 publications

(5 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The problem of a single item capacitated lot-sizing in flow shop, considering energy aspects, was studied in [59]. In this paper, two mixed integer programming models were developed in order to minimize the total production cost consisting of electrical, holding, setup, and power demand costs.…”

Section: Flow Shopmentioning

confidence: 99%

A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems

Renna

Materi

2021

Applied Sciences

View full text Add to dashboard Cite

Climate change mitigation, the goal of reducing CO2 emissions, more stringent regulations and the increment in energy costs have pushed researchers to study energy efficiency and renewable energy sources. Manufacturing systems are large energy consumers and are thus responsible for huge greenhouse gas emissions; for these reasons, many studies have focused on this topic recently. This review aims to summarize the most important papers on energy efficiency and renewable energy sources in manufacturing systems published in the last fifteen years. The works are grouped together, considering the system typology, i.e., manufacturing system subclasses (single machine, flow shop, job shop, etc.) or the assembly line, the developed energy-saving policies and the implementation of the renewable energy sources in the studied contexts. A description of the main approaches used in the analyzed papers was discussed. The conclusion reports the main findings of the review and suggests future directions for the researchers in the integration of renewable energy in the manufacturing systems consumption models.

show abstract

Section: Flow Shopmentioning

confidence: 99%

A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems

Renna

Materi

2021

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Jans and Degraeve (2008) gave an extensive overview of developed models in the area of deterministic dynamic lot sizing problems with the assumption of fixed demand and processing times. Considering the energy constraint, Masmoudi et al (2015, 2017) explored a particular case of DLSPP. First work (Masmoudi et al , 2015) proposed non-linear and linear mixed integer programming to optimize the total lot-sizing problem for flow shop system, by minimizing the costs of power demand, electrical, set-up and inventory.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Considering the energy constraint, Masmoudi et al (2015, 2017) explored a particular case of DLSPP. First work (Masmoudi et al , 2015) proposed non-linear and linear mixed integer programming to optimize the total lot-sizing problem for flow shop system, by minimizing the costs of power demand, electrical, set-up and inventory. They provided that non-linear problem formulation is able to determine the optimal lot-size solution in reasonable time by using CPLEX solver (Shinano et al , 2007; Bliek et al , 2014).…”

Section: Literature Reviewmentioning

confidence: 99%

Risk analysis for lot-sizing and maintenance optimization problem under energy constraint with subcontractor solution

Kammoun

Hajej

Rezg

2020

IJQRM

View full text Add to dashboard Cite

PurposeThe main contribution of this manuscript is to suggest new approaches in order to deal with dynamic lot-sizing and maintenance problem under aspect energetic and risk analysis. The authors introduce a new maintenance strategy based on the centroid approach to determine a common preventive maintenance plan for all machines to minimize the total maintenance cost. Thereafter, the authors suggest a risk analysis study further to unforeseen disruption of availability machines with the aim of helping the production stakeholders to achieve the obtained forecasting lot-size plan.Design/methodology/approachThe authors tackle the dynamic lot-sizing problem using an efficient hybrid approach based on random exploration and branch and bound method to generate possible solutions. Indeed, the feasible solutions of random exploration method are used as input for branch and bound to determine the near-optimal solution of lot-size plan. In addition, our contribution to the maintenance part is to determine the optimal common maintenance plan for M machines based on a new algorithm called preventive maintenance (PM) periods means.FindingsFirst, the authors have funded the optimal lot-size plan that should satisfy the random demand under service level requirement and energy constraint while minimizing the costs of production and inventory. Indeed, establishing a best lot-size plan is to determine the appropriate number of available machines and manufactured units per period. Second, for risk analysis study, the solution of subcontracting is proposed by specifying a maximum cost of subcontractor in the context of a calling of tenders.Originality/valueFor maintenance problem, the originality consists in regrouping the maintenance plans of M machines into only one plan. This approach lets us to minimize the total maintenance cost and reduces the frequent breaks of production. As a second part, this paper contributed to the development of a new risk analysis study further to unforeseen disruption of availability machines. This risk analysis developed a decision-making system, for production stakeholders, in order to achieve the forecasting lot-size plan and keeps its profitability, by specifying the unit cost threshold of subcontractor in the context of a calling of tender.

show abstract

“…These types of methods are mainly based on anticipated production planning through optimization algorithms. The most popular techniques for this purpose are linear programming in its different forms: integer [4]; binary [5], [6]; mixed [7]- [9]; dynamic [10]- [13]. There are also other techniques such as: particle swarm optimization [14], [15]; evolutionary algorithms [16]; game theory [17]; stochastic programming [18]; or the approach in which a battery energy storage system (BESS) is coupled with the main energy source to optimize the peak demand as in [19], [20].…”

Section: Introductionmentioning

confidence: 99%

A Peak Demand Control Algorithm for Multiple Controllable Loads in Industrial Processes

Martinez-Godoy¹,

Martell

Sánchez‐Chávez

et al. 2021

IEEE Access

View full text Add to dashboard Cite

The peak demand or demand limit control is an important part of the actions that industries carry out to optimize their energy consumption and reduce the costs related to their electricity billing. Prioritized switching of multiple appliances is often needed in order to reduce demand and energy consumption during peak load periods. The present article describes a peak load limitation algorithm that estimates the optimal disconnection time for one or more electrical loads before the electric demand exceeds a preset limit. This algorithm uses parametric and variable load factors that vary dynamically depending on what loads are present at a given time. For its validation, a software-in-the-loop testbed was designed and developed, in which multiple electrical loads were simulated via LabVIEW software and connected to a PLC controller emulated through CODESYS software. In this environment, several test configurations were executed and evaluated to study the influence of variables such as the nominal power and the disconnection priority of loads in the algorithm output. The results showed that the control algorithm is effective for peak load limitation, the maximum demand value reached during simulations tests did not exceed the preset demand limit at any time interval. The performance of the algorithm could be improved when prioritizing the shutdown of loads with higher nominal power or when increasing the anticipation time used for the disconnection of the controllable loads.INDEX TERMS Demand response, demand side management, load levelling, peak shaving, smart grid.

show abstract

Lot-sizing in flow-shop with energy consideration for sustainable manufacturing systems

Cited by 19 publications

References 20 publications

A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems

A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems

Risk analysis for lot-sizing and maintenance optimization problem under energy constraint with subcontractor solution

A Peak Demand Control Algorithm for Multiple Controllable Loads in Industrial Processes

Contact Info

Product

Resources

About