Simulating production and inventory control systems: a learning approach to operational excellence

Background: The high number of purchases created various impacts. It delayed other activities of RMSc CB operations. Inventory management staff had to spend most of working time for the procurement of supplies. This time constraint had affected the inventory control. In 2001, RMSc CB applied for the ISO/IEC 17025 accreditation. The nonconformance to the quality assurance system was found in the area of inventory management particularly in inventory control. The inventory scientific equipment control involve keeping detailed record on each piece of equipment, including such information were serial numbers, date the equipment was purchased, price, location, agency etc. The control and maintenance of scientific equipment supplies according to the quality assurance system had not been in place. The actual coding numbers labeled on scientific equipment were still the old numbers that were not matched with the number in the record of durable articles developed in 2001. Some equipment had not even been labeled with any numbers at all. This was not compliant to the quality assurance inventory control according to SENAC system (Scientific Equipment Name and Coding number system). The high number of purchases created various impacts. It delayed other activities of RMSc CB operations Inventory Staff had to spend most of working time for the procurement of supplies. This time constraint had affected the inventory control. Scientific equipment had not been controlled by SENAC system of the quality assurance system. This problem presented during 1999-2001 but no actions were done. According to the RMSc CB’s Vision in 2005, laboratory analysis should apply for ISO/IEC 17025 accreditation, Non-conformances have been found every time of the inspection for ISO/IEC 17025 accreditation of RMSc CB. More importantly, it had caused problems. Therefore, these problems had to be addressed as an urgent basis. This was based on the concept of work model according to “Open System Theory” of Robbins and Coulter, 1999, So that the working team was established to address the problems. They conduced a study in effort to find solution using SWOT analysis and solving problem. Objective: The goal of the project is to enhance the effectiveness of inventory management system of RMSc CB through the development of inventory procurement; inventory control; and improvement of related staff performance in order to achieve the following objectives. Methods: The project was implemented during 6 month consisting of 3 phases. The first phase focuses on preparation by reviewing existent inventory management system, planning and goal setting ,and design and developing supply and inventory management system. During the second phase the inventory staff’s had been trained and new system was tested. The last phase was an evaluation. Data were collected using both qualitative and qualitative methods including the use of survey, observation and in depth interviews. Results: The study found that the knowledge and skill of inventory staff have increased. The drop of annual number of the office supply purchase in 2003 reached the target of decreased of 50 percentage. And the coding numbers of all scientific equipment were matched and update with the ones in the inventory control system. The satisfaction levels of RMSc CB staff have increased as well. Conclusion: The project was successful in implementation. The evaluation program provided information about the results of the training in term’s knowledge and skills of inventory staff have increased. New inventory systems management could be decrease frequency purchase office supplies and error scientific equipment coding number. That could ultimately enhance staff’s satisfaction. However the overall program performance could be further improved.

While the net present value (NPV) approach is widely accepted as the right framework for studying production and inventory control systems, average cost (AC) models are more widely used. For the well known EOQ model it can be verified that (under certain conditions) the AC approach gives near optimal results, but does this also hold for more complex systems? In this paper it is argued that for more complex systems, like multi-source systems, one has to be extremely careful in applying the AC approach on intuition alone, even when these systems are deterministic. Special attention is given to a two-source inventory system with manufacturing, remanufacturing, and disposal, and it is shown that for this type of models there is a considerable gap between the AC approach and the NPV aprroach.

An NPV and AC analysis of a stochastic inventory system with joint manufacturing and remanufacturing

PurposeThe 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/approachThe 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.FindingsThe 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/implicationsThis research is limited to the dynamics of single-echelon production-inventory control systems with zero desired inventory level.Originality/valueThis 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.

This paper investigates the benefits of integrating advance demand information (ADI) with pull-kanban type production and inventory control systems (PICS). Since efficient analytical models for performance evaluation studies of these systems are unavailable, we use simulation experiments for the study. In particular, we investigate the impact of several PICS design parameters such as kanban card limits, target finished goods inventory levels, amount of demand information available, and the quality of ADI on performance measures such as system throughput, inventory holding costs and customer service levels. Our study shows that in many situations, integrating ADI with pull systems provides opportunities for efficiencies that might be significantly greater that that available using pull systems alone. Further more, we show that the performance of systems operating under pull-type PICS with ADI could be fairly robust to the quality of information being shared. 1

An Automatic Pipeline, Inventory and Order Based Production Control System (APIOBPCS), which is firstly proposed by Towill in 1982, lies at the heart of many commercial and bespoke ordering systems based on periodic review of stock and production targets. This simple and elegant control system works well, even when dealing with scenarios in which there are many competing value streams. However, when the demand is with time trend (such as ramp demand) rather than step changes, we show via linear s-transform analysis that there will be inventory drift in the APIOBPCS model. An innovative solution named PID-APIOBPCS model is proposed in this paper. In the new model, there are a PI controller in the inventory feedback loop which can eliminate the inventory drift and a PD controller in the order rate policy which can smooth the inventory level. At last, a simulation example is given to illustrate the benefit of PID-APIOBOBPCS model.

The theory of the control of stock is well understood, and a large number of firms use automatic stock control and ordering techniques as a major part of their inventory control systems. However, the effectiveness of such automatic stock control systems depends on the correct selection of system parameters for each item in the inventory and on the accurate reporting of information. It is not unusual for errors to be made in both the selection of parameters and the entry of data, and regular failures of either can cause severe problems in stock control. It is generally difficult for a human stock controller to discover errors quickly because of the large number of items that is usually found in a company inventory. This paper describes the use of an expert system to examine stock records and diagnose anomalies in the data provided or parameters applied to individual items in a stock control system. The expert system ‘reasons’ from symptoms such as reports from the forecasting system or high stock levels, to defects in the stock model used or data-collection processes, and from there to possible remedial action. Results are presented for runs of the expert system on a simulated stock control system.Key wordsartificial intelligenceexpert systemsstock controlsystem monitoring

This paper considers an inventory control system with a constraint on the service level. We focus on a popular service target in practice, the time-window ready rate, which is defined as the percentage of periods in which demands are completely fulfilled within a pre-specified time window. We explore the cost impact of different time-window ready rate settings by proposing evaluation and optimization methods for a single-location single-item min-max (or (s, S)) inventory system. New optimization procedures have been developed because the existing methods, which are based on a Lagrangian multiplier, cannot generally handle the current problem. More specifically, in some cases the time-window ready rate is a complicated function of the re-order point s, which renders existing algorithms inapplicable. Our algorithms are based on the monotone properties of cost and service constraint functions, which allow us to search the optimal policy efficiently within an identified region of policy-parameter values. Numerical experiments show the non-linear trade-off between cost and service, and indicate that extending or shrinking the time window can have a significant impact on the inventory cost.

Combined internal model and inferential control of a distillation column via closed-loop identification

The inventory control systems has an important role to monitor the condition of the goods at the supply chain stage of goods distribution from the central warehouse to retail in accordance with consumer demand. The research aims to develop inventory control systems on the supply chain distribution of goods from suppliers to retail through the central warehouse with minimal supply chain costs. Minimization of supply chain cost using martingale model of forecast evaluation, and the result as the basis for calculation of safety stock and reorder point. The results of research are the system that can be used to control inventory and renewal of goods in the central warehouse by calculating the minimization of supply chain cost based on consumer demand. Case studies were conducted on the supply chain distribution of goods from the central warehouse to the retail in Semarang. The observation data derived from the goods distribution from central warehouse to retail for certain products over 4 time periods. Through such inventory control system, can minimize supply chain cost, and product inventory level can be maintained in time and amount of inventory that must be fulfilled.

Increasing operating costs and decreasing net revenues have greatly underlined the importance of optimizing production operations. The development of automation systems in the Petroleum Industry has become important in uniting isolated production facilities to form integrated systems. This paper briefly traces the history and development of remote and computer control systems for gas and oil production. It also describes the development of the remote control and monitoring system installation at Union Oil onshore and offshore production facilities in East Kalimantan. Emphasis is placed more on the description of the remote process system monitoring and control in the Attaka field. The wireless communication and process control system are being used to transmit alarm and flow metering, emergency shutdown, and paging functions between five satellite wellhead platforms and production platform central monitoring system at the Attaka field. Each producing facility is designed to be compatible with remote supervisory control. To obtain this compatibility and a high degree of safety, conditions in each portion of the process system are monitored. Paralleling the development of automatic control techniques were computer applications. A simple computer system are being used to control and monitor three gas dehydration towers which comprise a portion of the Union LEX Plant operation at Santan onshore facility. Expectations and development of future systems and evaluation of past experience are discussed in the conclusion.

It is important to share demand information among the members in supply chains. In recent years, production and inventory systems with advance demand information (ADI) have been discussed, where advance demand information means the information of demand which the decision maker obtains before the corresponding actual demand arrives. Appropriate production and inventory control using demand information leads to the decrease of inventory and backlog costs. For a single stage system, the optimal base stock and release lead time have been discussed in the literature. In practical production systems the manufacturing system has multiple processes. The multiple stage production and inventory system with ADI, however, has been analyzed by simulation or assuming exponential processing time. That is, their theoretical analysis and optimization of release lead time and base stock level have little been obtained because of its difficulty. In this paper, theoretical analysis of a two-stage production inventory system with advance demand information is developed, where the processing time is assumed deterministic and identical; demand arrival process is Poisson, and an order base stock policy is adopted. Using the analytical results, optimal release lead time and optimal base stock levels for minimizing the average cost on the holding and backlog costs are explicitly derived.

In recent years, the correct management of inventories has become a fundamental pillar for achieving success in enterprises. Unfortunately, studies suggesting the investment and adoption of advanced inventory management and control systems are not easy to find. In this context, this article aims to analyze and present an extensive literature concerning inventory management, containing multiple definitions and fundamental concepts for the retail sector. A systematic literature review was carried out to determine the main trends and indicators of inventory management in Small and Medium-sized Enterprises (SMEs). This research covers five years, between 2015 and 2019, focusing specifically on the retail sector. The primary outcomes of this study are the leading inventory management systems and models, the Key Performance Indicators (KPIs) for their correct management, and the benefits and challenges for choosing or adopting an efficient inventory control and management system. Findings indicate that SMEs do not invest resources in sophisticated systems; instead, a simple Enterprise Resource Planning (ERP) system or even programs such as Excel or manual inventories are mainly used.

The manufacturing field is an area where the application of simulation is an essential tool for validating methods and architectures before applying them on the factory floor and the warehouse control. Multiagent system technology has demonstrated its utility in manufacturing system modelling and implementation. Agenthood features such as proactivity, reactivity, sociability and trust may also be useful for associating them with the specific simulation needs of the new manufacturing and warehouse management requirements. In this article, we present an agent-supported simulation tool for an intelligent manufacturing system and its influence with the management of the warehouse applied to a metal-mechanic manufacturing enterprise. The main goal is to provide a flexible simulation tool that can be adapted to solve the new manufacturing requirements and optimise and validate methods of management of material in warehouses that appear in real environments. Thus, the benefits of the multiagent theory application for the simulation of intelligent manufacturing and warehouse management system allows the experts of manufacturing domains to optimise the resource usage, control of inventory, providers and to have enough data to make decisions that influence the production level are presented.

Factors involved in computerizing the purchasing and inventory control functions in hospital pharmacies are described. When initiating an automated purchasing and inventory control system, a feasibility study should first be conducted to determine the extent of automation needed to develop a cost-effective system. The design of the system will depend on the extent to which the department of materials management is involved with other hospital departments. The advantages and disadvantages of decentralized versus centralized systems are discussed, and criteria for selecting hardware and software vendors are presented. A return-on-investment analysis should be performed to validate the benefits or savings expected from implementing the new automated system. Factors to consider during implementation of the new system and future developments affecting purchasing and inventory control systems, such as bar coding, are discussed. With the current concern about rapidly rising health-care costs and the need to enhance productivity, the development and implementation of automated purchasing and inventory control systems are important strategies for institutions to pursue now.