scholarly journals The effectiveness of single minute exchange of dies for lean changeover process in printing industry

2018 ◽  
Vol 154 ◽  
pp. 01064 ◽  
Author(s):  
Sri Indrawati ◽  
Mentari Endah Pratiwi ◽  
Sunaryo ◽  
Abdullah ‘Azzam

The changeover time is a factor that greatly affects the lean production implementation in industry with make to order system. Large product variations and unpredictable quantity of orders will trigger some kind of production wastes if changeover time is done in a longer time. One industry with make to order system is printing industry. In general, to produce several types of products such as books takes quite a long time because of long production changeover process. The general problem faced is the delay in book’s production completion. Based on this problem, changeover time reduction is needed to overcome the delay of book’s production completion using single minute exchanges of dies (SMED) method. The SMED method is the method that separates the changeover activity into two, i.e. internal setup and external setup. The research shows that changeover time for printing workstation is 18 minutes 29 seconds, which consists of internal setup activities 14 minutes 37 seconds and external setup 4 minutes 33 seconds. By converting 45% of the internal setup activity into an external setup, then the setup time can be reduced. The initial setup activities performed when machine is stop, now can be done when the machine is running. In addition, a changeover process improvement also done using 5S method in workstation tools area so the internal setup time is reduced 46% becomes 7 minutes 59 seconds. Under these conditions, the printing industry can increase production by 2%.

Author(s):  
Shanshan Li ◽  
Yong He ◽  
Li Zhou

AbstractThis paper considers a make-to-order system where production gets disrupted due to a random supply failure. To avoid potential stock-out risk and responding price increase during disruption, customers might decide to stockpile extra units for future consumption. We investigate the contingent sourcing strategy for the manufacturer to cope with the disruption. To this end, we first discuss the optimal post-disruption stockpiling decision for customers. In view of expected disruption duration, price rise, and inventory holding cost, three types of stockpiling behavior are analytically provided for the customers: non-stockpiling, gradual stockpiling, and instantaneous stockpiling. Next, a model is formulated to optimize the joint decision of contingent sourcing time and quantity, with the objective of maximizing profit expectation. Finally, by conducting numerical analysis, we generate further insights into the role of relative factors and provide specific managerial suggestions on how to adapt dynamic contingent sourcing strategies to alleviate different disruptions, under different market environments and customer behaviors.


2014 ◽  
Vol 27 (4) ◽  
pp. 534-560 ◽  
Author(s):  
Philipp Baumann ◽  
Salome Forrer ◽  
Norbert Trautmann

2012 ◽  
Vol 45 (6) ◽  
pp. 1493-1498 ◽  
Author(s):  
E. De Cuypere ◽  
K. De Turck ◽  
D. Fiems

2011 ◽  
Vol 209 (1) ◽  
pp. 159-178 ◽  
Author(s):  
Nasuh C. Buyukkaramikli ◽  
J. Will M. Bertrand ◽  
Henny P. G. van Ooijen

Author(s):  
Daria A. Edakina ◽  
◽  
Eduard I. Chernyak ◽  

The article highlights the almost unexplored issue of the classification of architectural heritage sites. The authors define architectural heritage as a complex of buildings and structures that form the surrounding space and reflect the art of creating these buildings and structures. Pursuing the goal to create a regulating system of Russian architecture monuments, the authors of the article use the architectural style as the main sign of monuments. Reliance on scientific research, written and visual sources allows identifying and characterizing large typological groups of monuments. The first group includes monuments of Russian architectural tradition, created in the period of 11th and 17th centuries on Byzantine and Italian architectural basis. The Baroque style was introduced into Russian architecture in the 18th century. It is characterizes by the magnificence and decorativeness of the details, includes columns, pilasters, sculptural decorations. About a century later, the Baroque was replaced by a style of Classicism. An obligatory element of Classicism monuments is a triangular gable, which rests on columns. Such compositional components as bays, risalitas, and balconies characterize the style. Monuments of classicism form architectural ensembles in Russian cities. The most famous of them is Palace Square in St. Petersburg. Since the mid-19th century, architectural monuments of the Eclectic style have been created. It combines elements of Gothic, Classicism, and folk Russian architecture. Wooden monuments of eclecticism, richly decorated with carvings, make the main pride of Tomsk. At the turn of the 19th and 20th centuries, modern architectural monuments with their characteristic asymmetry of the layout, plant decor in the design of facades are created. Under the influence of the changes brought by the Revolution of 1917, the style of Constructivism spreads in Russian architecture. In the early 1930s, the laconic Constructivism was rejected, the order system returned to the composition of the buildings. They are decorated with stucco moldings and sculptural images. For a long time unnamed, now this style is known as Soviet Neoclassicism. In the late 1950s, monuments of Soviet Neoclassicism were accused of unjustified pomp and parade. In the second half of the 20th century, the trends of Neo-Functionalism and Postmodernism prevail in Russian architecture. The regulating system of architectural monuments proposed in the article allows to characterize objects of architectural heritage, provides continuity of cultural experience.


2012 ◽  
Vol 8 (1) ◽  
pp. 63-74
Author(s):  
K. Kaanodiya ◽  
Mohd Rizwanullah

Minimize Traffic Congestion: An Application of Maximum Flow in Dynamic NetworksAn important characteristic of a network is its capacity to carry flow. What, given capacities on the arcs, is the maximum flow that can be sent between any two nodes? The dynamic version of the maximum flow problem on networks that generalizes the well-known static one. This basic combinatorial optimization problem has a large implementation for many practical problems. Traffic congestion is a consequence of the nature of supply and demand: capacity is time consuming and costly to build and is fixed for long time periods, demand fluctuates over time, and transport services cannot be stored to smooth imbalances between capacity and demand. In this paper, I tried to solve the traffic congestion problem i.e. Maximum flow of goods in a dynamic network with the help of a Lingo Model. The same can be generalized for the large product if the software supports the systems.


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