Optimization of Safety Stock under Controllable Production Rate and Energy Consumption in an Automated Smart Production Management

Abstract

A smart production system is essential to produce complex products under the consumption of efficient energy. The main ramification of controllable production rate, amount of production size, and safety stocks is simultaneously optimized under proper utilization of energy within a smart production system with a random breakdown of spare parts. Due to the random breakdown, a greater amount of energy may be used. For this purpose, this study is concerned about the optimum safety stock level under the exact amount of energy utilization. For random breakdown, there are three cases as production inventory meets the demand without utilization of the safety stock, with using of the safety stock, and consumed the total safety stock amount and facing shortages. After the random breakdown time, the smart production system may move to an out-of-control state and may produce defective items, where the production rate of defective items is a random variable, which follows an exponential distribution. The total cost is highly nonlinear and cannot be solved by any classical optimization technique. A mathematical optimization tool is utilized to test the model. Numerical study proves that the effect of energy plays an important role for the smart manufacturing system even though random breakdowns are there. it is found that the controllable production rate under the effect of the optimum energy consumption really effects significantly in the minimization cost. It saves cost regarding the corrective and preventive maintenance cost. The amount of safety stock can have more support under the effect of optimum energy utilization. The energy can be replaced by the solar energy.

An Automated Smart EPQ-Based Inventory Model for Technology-Dependent Products under Stochastic Failure and Repair Rate

“…The study introduces a discrete investment to improve production system reliability. For an automated smart production system, [2] investigated energy consumption and production costs under controllable production rates. The study suggests that the smart production system offers a better production strategy with a controllable production rate compared to conventional systems.…”

“…The following abbreviations are used in this paper. Technology dependent demand rate (units/unit time) C(µ, λ) Unit smart production cost, a function of manufacturing quality performance parameter and variable production rate ($/unit/unit time) r 1 Raw material cost ($/unit) r 2 Raw material increment cost due to low manufacturing quality performance parameter ($/unit) Y Unit manufacturing yield loss cost due to low manufacturing quality performance parameter ($/unit/unit time) Hence the expected cost is strictly convex and achieves optimal minimum value at Q * = 2985.27, µ * = 1081.51, λ * = 5.54 × 10 −6 , and τ * = 0.006.…”

“…In this regard, Ref. [2] investigated energy consumption and production costs under controllable production rates for an automated production control system. The study suggests that smart production system offers better production strategy with controllable production rate rather than conventional systems.…”

Effect of Electrical Energy on the Manufacturing Setup Cost Reduction, Transportation Discounts, and Process Quality Improvement in a Two-Echelon Supply Chain Management under a Service-Level Constraint

“…The supply chain is a complex process consisting of several parameters that need to be controlled. Among them, the few parameters that can be controlled by making some additional investments include the setup cost, lead time, and quality of the products, as shown by Sarkar and Sarkar [1]. Certain parts of the manufacturing units need to be improved with state-of-the-art technology to reduce the energy consumption and enhance the quality of the products.…”

An Application of Time-Dependent Holding Costs and System Reliability in a Multi-Item Sustainable Economic Energy Efficient Reliable Manufacturing System

“…This model fulfils the gap of multi-product in a SERMQ model where the holding costs are time-dependent and the model is solved using control theory. Recently, Sarkar and Sarkar [19] developed a smart production system with the effect of energy, but the main issue remains the same; using a traditional production system, how can an industry can make a sustainable energy efficient production system? There are several studies (Kluczek [20] and Harris et al [21], Dehning et al [22]) considering how smart production solved the issues of efficient energy and all other issues like waste management (Khalil et al [23], Nižetić et al [24], Biel and Glock [25]), but not all industries can adopt the smart production system.…”