A Review of the Implementation of JIT Algorithms and Models in Production Systems

Intense competition in today’s economy, the shrinking life cycles of products, and the heightening expectations of customers have forced business enterprises to focus their attention on correctly arranging and controlling their production and supply chain systems. Thus, manufacturing firms/industries adopt JIT techniques to enjoy competitive advantage. In this paper, a literature review is presented to show the important applications of JIT Algorithms and Models in Production Systems. The purpose of this step is to review the results obtained from the implementation and to provide the practical recommendations for further improvement. This will help reveal practical issues encountered in the implementation. All these issues should become main concerns if the manufacturing Plant wants to get maximum benefits from the JIT implementation. This study bridged a research gap by identifying a framework for re-design of manufacturing systems into practical optimum Just-In-Time systems. The conventional JIT approach is mostly applicable to static production systems and the dynamic production systems require a more practical integrated JIT approach

A comparative study of Just-In-Time (JIT) and Theory of Constraints (TOC) systems with varying constraint locations and operational characteristics

Various researchers have extolled the benefits of Theory of Constraints (TOC), Just-in-Time (JIT), and other manufacturing strategies. Some supporters of JIT argue it is the least costly, while others point to the overall benefits of TOC. There are conflicting claims as to the best manufacturing philosophies which is compounded by the fact that no one system is best in every situation. The success of a production system truly depends on the manufacturing environment rather than the philosophy being used. This study uses computer simulations of differing manufacturing environments to compare Just-in-Time (JIT) and Theory of Constraints (TOC) philosophies over two response variables, make span and work-in-process (WIP). Results showed significant differences favoring both TOC and JIT in different manufacturing environments with respect to both make span and work-in-process (WIP). The study showed evidence that both JIT and TOC are essentially the same when a production system has a bottleneck located at the last station. However, the performance of TOC could equal that of JIT with less inventory. This supports the concept of strategic inventory use for the constrained resource in TOC over the JIT concept of having at least two Kanban cards at each workstation. Different process structures showed different performance for the two strategies used. The study suggested that higher setup and process variation did not have much effect on WIP level, but they did have a significant effect on the make span variable. In conclusion, the study proved that not one system is best in every condition. Each manufacturing environment will be best served by a unique manufacturing strategy --Abstract, page iii

PROPOSED CONCEPTUAL FRAMEWORK OF INVENTORY MANAGEMENT USING THE JUST-IN-TIME (JIT) PHILOSOPHY

The effectiveness of the proposed JIT inventory management model, while conceptually developed based on previous case studies, depends largely to both internal and external support mechanisms of the organization. While the JIT philosophy has manifested remarkable contributions to productivity and efficiency in the developed countries, much has yet to be gained from it in the developing countries. Some problems can confound the adoption and implementation of JIT in the third world.Sector, as in the case of Tanzania (Msimangin, 1993): financial constraints, inadequate supply of inputs required for the production mills to operate near capacity, international delivery delays, an inadequate transportation infrastructure, and unreliable product demand forecasts. These problems are also present in the Philippines. Zamora (1989) identified several additional problems encountered in the implementation of JIT components in the Philippine setting: resistance to change, socio-cultural barriers, and lack of training, The success of any model or framework using the JIT philosophy must address these prob- j lems firmly. As in other cases, the successfti implementation of the proposed inventory management framework using the JIT philosophy could be achieved if existing local conditions aw considered to suit the requirements of the model] Flexibility of model adoption is therefore necessary.Further, it is recommended that the proposed model be practically applied in applicable situations and empirical informal be obtained to improve the framework. In this sense, the proposed model will be tested as to its practical usefulness apart from being conceptual

Competitiveness of Indian Manufacturing: Finding of the 2001 National Manufacturing Survey

In this paper we present findings of the second national survey on the competitiveness of Indian manufacturing. The paper develops hypotheses on the competitiveness of firms in the manufacturing sector and addresses some key questions on the characteristics of world class firms in India. We analyze the processes and practices that such firms have adopted to become world class. More important, we highlight firm level practices that are preventing Indian firms from becoming globally competitive. The findings point towards three distinct aspects of manufacturing management that define the capabilities of the firm, i.e., strategies related to dynamic control of shop floors, network linkages and innovation. It is found that firms that build distinctive technological and managerial capabilities in these domains are able to compete globally. The paper provides a comparison with manufacturing capabilities of competitors in China and draws lessons for organizing large scale manufacturing. It also provides an assessment of the changes that have happened in manufacturing priorities and strategies in India since our last survey that was conducted in 1997 and highlights the implications of these changes.

Stochastic Lot Sizing for Shareholder Wealth Maximisation under Carbon Footprint Management

Fulltext in http://www.jiii.org/index.php?m=content&c=index&a=show&catid=41&id=141There is a growing consensus that human beings must cut greenhouse gas emissions to mitigate global warming and the resultant impacts on the environment. However, production optimisation has rarely taken this issue into consideration, often leading to environmentally unsustainable operation decisions. This paper presents a lot sizing batch optimisation model for a stochastic make-to-order production environment under the carbon emission trading mechanism—currently the most effective market-based carbon emission controlling system, with an aim to maximise the long-term sustainable interests of corporate owners, well-known as the shareholder wealth. To more closely reflect the real-world manufacturing environment, the proposed model adopts general distributions, instead of unrealistic theoretical assumptions, for random variables. We apply the model to investigate the impacts of the carbon emission trading mechanism on shareholder wealth, and test its hedging capability against a series of risk factors. The analytical results provide insights into production optimisation with carbon footprint management.International Conference on Industrial Engineering and Applications (ICIEA 2014), Sydney, Australia, 29-30 May 2014. In Journal of Industrial and Intelligent Information, 2015, v. 3 n. 1, p. 1-

Constraint-Based Supply Chain Inventory Deployment Strategies

The development of Supply Chain Management has occurred gradually over the latter half of the last century, and in this century will continue to evolve in response to the continual changes in the business environment. As organizations exhaust opportunities for internal breakthrough improvements, they will increasingly turn toward the supply chain for an additional source of untapped improvements. Manufacturers in particular can benefit from this increased focus on the chain, but the gains realized will vary by the type of supply chain. By applying basic production control principles to the chain, and effectively using tools already common at the production line level, organizations address important supply chain considerations. Both the Theory of Constraints and the factory physics principles behind the Constant WIP concepts focus on the system constraint with the aim of controlling inventory. Each can be extrapolated to focus on a system whose boundaries span the entire supply chain

Determining Kanban Size Using Mathematical Programming and Discrete Event Simulation for a Manufacturing System with Large Production Variability

In order to become more competitive and aggressive in the market place it is imperative for manufacturers to reduce cycle time, limit work-in-process, and improve productivity, responsiveness, capacities, and quality. One manner in which supply chains can be improved is via the use of kanbans in a pull production system. Kanbans refer to a card or signal for productions scheduling within just-in-time (JIT) production systems to signal where and what to produce, when to produce it, and how much. A Kanban based JIT production system has been shown to be beneficial to supply chains for they reduce work-in-process, provide real time status of the system, and enhance communication both up and down stream. While many studies exist in regards to determining optimal number of kanbans, types of kanban systems, and other factors related to kanban system performance, no comprehensive model has been developed to determine kanban size in a manufacturing system with variable workforce production rate and variable demand pattern. This study used Stewart-Marchman-Act, a Daytona Beach rehabilitation center for those with mental disabilities or recovering from addiction that has several manufacturing processes, as a test bed sing mathematical programming and discrete event simulation models to determine 2 the Kanban size empirically. Results from the validated simulation model indicated that there would be a significant reduction in cycle time with a kanban system; on average, there would be a decrease in cycle time of nine days (almost two weeks). Results were discussed and limitations of the study were presented in the end