scholarly journals The Impact of Feedback Information on Dynamics Performance of Production-Inventory Control Systems

2021 ◽  
Author(s):  
Huthaifa AL-Khazraji ◽  
Colin Cole ◽  
William Guo
Keyword(s):  
Control System ◽  
Control Systems ◽  
Inventory Control ◽  
Bullwhip Effect ◽  
Absolute Error ◽  
Feedback Information ◽  
Simulation Based ◽  
Production Inventory ◽  
Beneficial Impact ◽  
The Impact

The aim of this paper is to examine the beneficial impact of feedback information in the dynamics of production-inventory control systems. Two production-inventory control system models are analyzed: APIOBPCS and 2APIOBPCS models. The simulation-based experiment designs were conducted by using the state-space equations of the two models. The bullwhip effect as measured by the variance ratio between the order rate and the consumption rate, and inventory responsiveness as measured by the Integral of Absolute Error between the actual and the target levels of inventory, are two metrics used to evaluate the performance of the production-inventory control system in response to a random customer demand. To ensure that both models work under optimal performance, multi-objective particle swarm optimization (MOPSO) is employed to address the problem of tuning the controller’s parameters. The simulation results show the 2APIOBPCS model outperforms the APIOBPCS model at achieving the desired bullwhip effect and being able to provide better inventory responsiveness. The improvement in the inventory responsiveness becomes more significant when the system operates under mismatched lead time and/or an initial condition.

Analysing the impact of different classical controller strategies on the dynamics performance of production-inventory systems using state space approach

2018 ◽  
Vol 13 (1) ◽  
pp. 211-235 ◽  
Author(s):  
Huthaifa AL-Khazraji ◽  
Colin Cole ◽  
William Guo
Keyword(s):  
Control System ◽  
State Space ◽  
Inventory Control ◽  
Bullwhip Effect ◽  
Inventory Level ◽  
State Space Approach ◽  
Content Type ◽  
Production Inventory ◽  
The Impact ◽  
Space Approach

Purpose The purpose of this paper is to examine the impact of applying two classical controller strategies, including two proportional (P) controllers with two feedback loops and one proportional–integral–derivative (PID) controller with one feedback loop, on the order and inventory performance within a production-inventory control system. Design/methodology/approach The simulation experiments of the dynamics behaviour of the production-inventory control system are conducted using a model based on control theory techniques. The Laplace transformation of an Order–Up–To (OUT) model is obtained using a state-space approach, and then the state-space representation is used to design and simulate a controlled model. The simulations of each model with two control configurations are tested by subjecting the system to a random retail sales pattern. The performance of inventory level is quantified by using the Integral of Absolute Error (IAE), whereas the bullwhip effect is measured by using the Variance ratio (Var). Findings The simulation results show that one PID controller with one feedback loop outperforms two P controllers with two feedback loops at reducing the bullwhip effect and regulating the inventory level. Originality/value The production-inventory control system is broken down into three components, namely: the forecasting mechanism, controller strategy and production-inventory process. A state-space approach is adopted to design and simulate the different controller strategy.

Multi-objective particle swarm optimisation approach for production-inventory control systems

2018 ◽  
Vol 13 (4) ◽  
pp. 1037-1056 ◽  
Author(s):  
Huthaifa AL-Khazraji ◽  
Colin Cole ◽  
William Guo
Keyword(s):  
Control System ◽  
Control Systems ◽  
Inventory Control ◽  
Dynamic Performance ◽  
Particle Swarm ◽  
Particle Swarm Optimisation ◽  
Inventory Level ◽  
Content Type ◽  
Multi Objective ◽  
Production Inventory

Purpose This paper aims to optimise the dynamic performance of production–inventory control systems in terms of minimisation variance ratio between the order rate and the consumption, and minimisation the integral of absolute error between the actual and the target level of inventory by incorporating the Pareto optimality into particle swarm optimisation (PSO). Design/method/approach The production–inventory control system is modelled and optimised via control theory and simulations. The dynamics of a production–inventory control system are modelled through continuous time differential equations and Laplace transformations. The simulation design is conducted by using the state–space model of the system. The results of multi-objective particle swarm optimisation (MOPSO) are compared with published results obtained from weighted genetic algorithm (WGA) optimisation. Findings The results obtained from the MOPSO optimisation process ensure that the performance is systematically better than the WGA in terms of reducing the order variability (bullwhip effect) and improving the inventory responsiveness (customer service level) under the same operational conditions. Research limitations/implications This research is limited to optimising the dynamics of a single product, single-retailer single-manufacturer process with zero desired inventory level. Originality/value PSO is widely used and popular in many industrial applications. This research shows a unique application of PSO in optimising the dynamic performance of production–inventory control systems.

Dynamics analysis of a production-inventory control system with two pipelines feedback

Kybernetes ◽  
2017 ◽  
Vol 46 (10) ◽  
pp. 1632-1653
Author(s):  
Huthaifa AL-Khazraji ◽  
Colin Cole ◽  
William Guo
Keyword(s):  
Control System ◽  
Dynamic Model ◽  
Inventory Control ◽  
Production Control ◽  
Bullwhip Effect ◽  
Inventory Level ◽  
Content Type ◽  
Production Control System ◽  
Customer Service Level ◽  
Production Inventory

Purpose The purpose of this study is to propose a new dynamic model of a production-inventory control system. The objective of the new model is to maximise the flexibility of the system so that it can be used by decision makers to design inventory systems that adopt various strategies that provide a balance between reducing the bullwhip effect and improving the responsiveness of inventory performance. Design/methodology/approach The proposed production-inventory control system is modelled and analysed via control theory and simulations. The production-inventory feedback control system is modelled through continuous time differential equations. The simulation experiments design is conducted by using the state-space model of the system. The Automatic Pipeline Inventory and Order-Based Production Control System (APIOBPCS) model is used as a benchmark production-inventory control system. Findings The results showed that the Two Automatic Pipelines, Inventory and Order-Based Production Control System (2APIOBPCS) model outperforms APIOBPCS in terms of reducing the bullwhip effect. However, the 2APIOBPCS model has a negative impact on Customer Service Level. Therefore, with careful parameter setting, it is possible to design control decisions to be suitably responsive while generating smooth order patterns and obtain the best trade-off of the two objectives. Research limitations/implications This research is limited to the dynamics of single-echelon production-inventory control systems with zero desired inventory level. Originality/value This present model is an extension and improvement to Towill’s (1982) and John et al.’s (1994) work, since it presents a new dynamic model of a production-inventory control system which utilises an additional flow of information to improve the efficiency of order rate decisions.

Reducing the Impact of Source Information Uncertainty in Intelligent Automated Thermal Process Control Systems in Ensuring Reliable Operation of Power Equipment

Vestnik MEI ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 78-87
Author(s):  
Edik K. Arakelyan ◽  
◽  
Ivan A. Shcherbatov ◽  
Keyword(s):  
Control System ◽  
Process Control ◽  
Control Systems ◽  
Process Control System ◽  
Power Equipment ◽  
Source Information ◽  
Equipment Operation ◽  
Process Control Systems ◽  
Automated Process ◽  
The Impact

The uncertainty of the source information is used to solve key tasks in an intelligent automated thermal process control system affects the calculation of control actions, the implementation of equipment optimal operating modes and, as a result, leads to degraded reliability. As a rule, this type of information can be qualitative (the use of expert knowledge) or quantitative in nature. In this regard, it is extremely important to reduce the impact of uncertainty. The aim of the study is to identify the types and origins of uncertainty in the source information used by an intelligent automated process control system and to develop approaches to reduce its impact on the reliability of power equipment operation. The approaches used to ensure the specified indicators of reliability, efficiency and environmental friendliness in modern intelligent automated process control systems are based on predictive strategies, according to which the technical condition of equipment and specific degradation processes are predicted. This means that various types of uncertainty can have a significant negative impact. To reduce the influence of uncertainty of the initial information that affects the reliability of power equipment operation, the use of artificial neural networks is proposed. Their application opens the possibility to predict the occurrence of equipment defects and failures based on retrospective data for specified forecast time intervals. A method for reducing the impact of anomalies contained in the source information used in an intelligent process control system for energy facilities is demonstrated. Data omissions and outliers are investigated, the elimination of which reduces the impact of uncertainty and improves the quality of solving key problems in intelligent automated process control systems. Experimental studies were carried out that made it possible to identify the mathematical methods for removing omissions and anomalies in the source information in the best way. Methodological aspects of eliminating various types of uncertainty that exist in managing of power facilities by means of intelligent automated process control systems at the key stages of the power equipment life cycle are described.

Two Major Antecedents of Salesforce Motivation: Salesforce Control Systems and Compensation Plans

2017 ◽  
Vol 49 (2) ◽  
pp. 87-101 ◽  
Author(s):  
Zoha Fatima
Keyword(s):  
Control System ◽  
Control Systems ◽  
Extrinsic Motivation ◽  
Future Research ◽  
Compensation Plans ◽  
Two Factors ◽  
Salesforce Compensation ◽  
The Impact

Salesforce motivation is important for the success of the organization. Unless and until the salesforce is motivated, the organization will not be able to prosper. There are various factors that are responsible for salesforce motivation. It has been found that out of these many factors, the impact of salesforce control system and salesforce compensation plans is inevitable. Therefore, this study makes an attempt to analyze the impact of these two factors on salesforce motivation by following a review of selected studies from the year 1977 to 2014. Till now, none of the previous studies have analyzed the impact of these two factors on motivation. The review of studies reveals that salesforce control systems and compensation plans should be taken into consideration when motivation of salespeople is talked about as they have an impact on intrinsic as well as extrinsic motivation of salespeople. Based on the findings of the review, a framework is designed and implications and directions for future research are stated.

Functionalities of production-inventory control systems

1991 ◽  
Vol 2 (3) ◽  
pp. 219-227 ◽  
Author(s):  
J. MAES ◽  
L. N. VAN WASSENHOVE
Keyword(s):  
Control Systems ◽  
Inventory Control ◽  
Production Inventory

scholarly journals The impact of foreign markets globalization on the price and functionality of electronic access control systems

2021 ◽  
Vol 92 ◽  
pp. 07009
Author(s):  
Martin Boroš ◽  
Filip Lenko ◽  
Andrej Velas
Keyword(s):  
Control System ◽  
Access Control ◽  
Control Systems ◽  
Value Added ◽  
European American ◽  
Foreign Markets ◽  
Access Control System ◽  
Electronic Access ◽  
The Impact

Research background: The research, which is the subject of the paper, is based on the global expansion of the use of electronic access control systems using biometric data for user verification. Due to the globalization of products from foreign markets to Slovakia, there is a competition between suppliers. The disadvantage is that organizations that are considering procuring an electronic access control system focus their attention only on its price. Globalization and global use have neglected the skills gap between European, American, and Asian markets. Purpose of the article: The paper will aim to point out, through a case study, the financial and functional differences of electronic access control systems. In the case study, a comparison of three different systems with the possibility of procurement on the European, American, and Asian markets will be performed on the building - administrative building. Methods: The article will mainly use methods such as the global method and the optimization model of the financial plan. As well as a case study, the cooperation of achieved results and analysis of possibilities of foreign markets. Findings & Value added: The results achieved by the paper will be globally usable in the conditions of European countries. These will be the conclusions of a case study that will point to the appropriateness of choosing an electronic access control system using biometric features in a standard office building. We can also consider the creation of a project budget usable for organizations as one of the added values.

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