DEVELOPING SMART WASTE INDENTIFICATION SYSTEM FOR TRANSPORTATION OF GOODS FOR MANUFACTURING INDUSTRIES BASED ON LEAN PRINCIPLES

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DEVELOPING SMART WASTE INDENTIFICATION SYSTEM FOR TRANSPORTATION OF GOODS FOR MANUFACTURING

INDUSTRIES BASED ON LEAN PRINCIPLES

Foon-Siang Low^1*, Zhi-Hao Yee² and Heap-Yih Chong³

12 Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, MALAYSIA

3 School of Design and the Built Environment, Curtin University, Perth, AUSTRALIA

*Corresponding author: [email protected] Accepted: 12 February 2020 | Published: 6 March 2020

Abstract: Lean principle is a concept of eliminating waste by reducing non-value-added activities and increase value added operation. Waste in transportation often relates to the unnecessary distance travelled, excess time and cost that incurred. Previous studies rarely focus on the application of the lean principle in reducing transportation cost. Hence, this research aims to develop a smart waste identification lean system for improving transportation operation costs based on lean principle. A case study was conducted in a manufacturing firm to study the effectiveness of the tool in identifying and reducing the transportation waste. The results show that waste do exists in terms of transportation operation in the company and this will affect the performance of the company. The company would take excess amount of time for delivering their products. In conclusion, the developed tool has been proven in improving the logistics performance through the waste reduction.

Keywords: Lean Principle, Transportation, Waste Identification System, Developing Software

1. Introduction

Lean concept had a very long history where the origin of the concept could be traced back to 1450s in Venice. This very first lean manufacturing revolution was brought by a person name Henry Ford back in 1913. In the year of 1913, Henry Ford, the founder of an American Automobile company, Ford Motor Company introduces the mass production technique that revolutionized the car manufacturing industry. Henry Ford create the flow production system by synthesized the interchangeable parts with standard work and moving conveyor when designing the production line of model T automobile (Swan, 2013). The principles of assembly are (1) Man and tools are to be place in sequence so that the distance travel by each of component is minimum; (2) Use work slides or carrier so that the worker can always put the part back to the same place after the operation and the place must be a convenient place for the worker and if possible let the gravity do the job to carry the part to the next worker; (3) Use sliding assembling lines to deliver the assembly part at convenient distance (Ford & Crowther, 1922). However, this system was lack of flexibility and

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had limited variety. All the model T automobile produces are limited to one specification and they are all identical. One of the big motor companies, Toyota, has been leading in global market for many years and replaced General Motors to be the largest automaker in global since 2008 (Wee &

Wu, 2009). After second world war, Toyota learnt the concept of Ford’s manufacturing from ford Henry book, Today and Tomorrow. Toyota executive, Taiichi Ohno with backing from Eiji Toyoda help to establish Toyota Production System (TPS) based on Sakichi Toyoda ‘Jidoka’ and Kiichiro Toyoda ‘Just-in-Time’ concept to achieve the goal of reducing the production cost, improve product’s quality and increase throughput times (Ohno, 1988). In the TPS, it relies on few concepts; one of them is eliminating the waste. The rest of the concepts include non-value added (NVA) work, pull system, U-shaped cells, Single-Minute Exchange of Dies (SMED) and one- piece flow (Murray, 2016). MIT professors introduced the word “lean” to interpret Japan’s new production system which deviated from conventional mass production system as mass production will cause waste (Wee & Wu, 2009). Lean defined as tool to eliminate the waste by reducing NVA operation and improves value added (VA) operation. Taiichi Ohno was the first person whom identifies the seven types of waste (MUDA), which are overproduction, over-processing, inventory, transportation, defects, motion and waiting (Martin & Osterling, 2017). Waste is the extra actions or processes that do not add any value to the product or customer. The very first step of lean thinking is to understand and define what is value and the necessary step to create the value (Jones & Saad, 1998). Once the value is identified, any operation that does not add value are consider as waste as it will consume the resources and causing extra cost to be incurred. The fundamental of this concept is to eliminate the waste and optimize the usage of resources available (Malihe et al, 2014).

Transportation is considered as one of the seven wastes under lean principles; however, it is necessary to transport the products to the customer through transportation (Womack & Jones, 1999). By reducing the transportation waste such as extra loading or unloading time and extra distance travel, a company will be able to save a certain amount of production cost and the products are able to be delivered to the customer faster and on time. Lean principle is an alternative approach in eliminating transportation waste by utilizing the lean transportation metrics (Villarreal et al, 2017). As compare to the other methods such as mathematical modeling, it is more reliable as it does not rely on the estimated parameters. Lean concept focus on eliminate NVA and improve VA operations in order to improve the efficiency in an operation (Tsasis & Bruce, 2008). These is achieved by identifying the flow of the operation, specific actions and solutions are taken to improve the flow of the operation rather than relying on the oversimplified parameters that may not be suffice to represent or define the real-life scenario (Villarreal, 2016). Furthermore, lean approach in this study also provides a lower cost solution as no experiment or simulation needs to be conducted and no special equipment is required as well. A company always in search for the most efficient and cost-effective way to improve and this lean tool provides the company a cheap and effective way to tackle the transportation waste. Although lean principle is a powerful tool to reduce and minimize the waste (Shah et al, 2015), some companies are still not aware about the benefits of implementing lean ideology in their companies. They worry that implementing lean would be costly and does not provide any advantages (Nakajima, 1988). In Malaysia, the possibility of implementing lean principles depends on the size of the company (McKinnon & Ge, 2006). Large companies are more likely to implement lean principles in their company and smaller

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companies are less likely to do so. Waste can be found in the transportation operation and additional costs will normally incur ((McKinnon & Ge, 2006). This indirectly reduces the company’s profit. In some extreme cases, the company is suffering loss as it exceeds the budget.

Lean principles have been implemented in industries to improve the efficiency and reduce cost, however, the research on application of lean principles and lean metric to eliminate the waste in transportation is rather limited (Villarreal, 2009). Most of existing researches may focus on inventory or production line management based on lean principles in manufacturing industry and not so much on the logistics of goods (Yap et al, 2018). There is a lack of useful examples that can be used as reference to tackle the transportation waste in manufacturing industry. Even though there are some other approaches to eliminate transportation waste and problems such as mathematical modeling, simulation and researches on operations, many still doubt the effectiveness of these methods in addressing the real life transportation problems (Berhan, 2014).

Thus, this research aims to develop a smart waste identification lean system for improving transportation operation costs based on lean principle. The objectives of this study are 1) To identify the flaws that exist in the transportation system of manufacturing industry, and 2) Develop a smart waste identification system to eliminate the waste and improve the efficiency of the industry. Lean principles will be used in this study and Total Overall Vehicle Effectiveness (TOVE) metric will be used to analyze the company transport operation (Simon et al, 2004). A lean smart identification software will be developed to identify the waste exists in the transport operations. The remaining parts of this paper are organized as follows: Section 2 reviews the related literature. Section 3 describes the methodology. Section 4 discusses the new applications from of the case studies. Section 5 discusses the research findings. Section 6 concludes the research significance, highlights its limitations, and future studies.

2. Literature Review

Eliminating Waste Based on Lean Concept

Based on lean concept, waste is something that will hinder a company from operating at its full potential. Application of lean concept in a company can helps to enhance the company competency and stay competitive by eliminating the waste which is also known as “MUDA” by Toyota (Shingo

& Dillon, 1989). The efficiency of the corporation can be improved by eliminating the waste (Womack & Jones, 1999). The seven types of waste exist in supply chain will reduce the efficiency of a company and the following are the seven types of waste (Sutherland & Bennett, 2008):

(i) Overproduction: Build more than order.

(ii) Waiting: Delay of activities.

(iii) Transportation: Any unnecessary transport.

(iv) Inventory: Extra inventory that resulted from logistic activities.

(v) Motion: Any extra movement.

(vi) Space: Use of space which is below optimal.

(vii) Error: Activities which cause rework, adjustment and return.

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Waste does not add any value to both the product and service (Hines & Taylor, 2000). Lean concept is principles, philosophies or processes that eliminate waste and add value to customers (Tsasis & Bruce, 2008; Ugochukwu et al, 2012). Lean helps eliminate the waste trough minimize NVA activities and maximize VA activities.

TPS will constantly eliminate the waste and improve the customer satisfaction (Pegels, 1984).

Transportation waste was identified as one type of waste under lean concept by Taichii Ohno in TPS. Waste and unnecessary cost can be found in the transportation (McKinnon & Ge, 2006).

Although lean concept has been expanded towards many areas in manufacturing industry, the application of lean concept to eliminate transportation waste is rather limited [30]. Most of the researches are mainly focusing on interpreting lean principle and benefits of implementing lean principle in manufacturing industry rather than providing a case study how lean principle helps to eliminate the waste in transportation.

Other approaches such as mathematical modeling and simulation method have been introduced to eliminate the transportation waste (Sternberg, 2013), however the effectiveness of these method are highly in doubt by many others (Berhan, 2014). The most significant reason that these methods fail to solve transportation waste problem is the parameters and factors they used in these methods such as distance, time and demands are oversimplified, whereby in real life situation they are stochastic (Ak & Erera, 2007). As a result, these methods rarely used to improve the transportation efficiency (Fugate, 2009).

An alternative solution, application of lean principles in eliminating the transportation waste may seem to be an opportunity to cope the weakness and limitation of the conventional methods. Lean principles emphasized on eliminating NVA operations, improving VA operations and maximize the efficiency of the company process flow (Tsasis, 2008). It analyzed the data from the process flow and specific action or activities will be taken to improve the smoothness of the flow. The data or feedback obtained from the process is more reliable as compare to the assumption made in other methods.

The ‘Five Steps Model’ explains the five necessary steps to improve the flows of the services and goods of a company (Womack & Jones, 1999). The very first step is to identify and define the

‘value’ that defined by the end user or customer. The second step is to identify the value stream of the operation. Value steam can be defined as necessary actions which are required to bring main flows essential to every product (Rother & Shook, 1999). VSM enables ones to have better visualization of the flow materials and information as the products flow through value stream.

Actions that create ‘waste’ can be identified through this step. This is also known as the process re-engineering to create a smooth ‘flow’ in next step. As waste was removed from the value stream, product and service can flow smoothly without any interruption, delays or bottleneck. A “pull”

system then can be established by the company itself, the goods or service can be “pull” by the customer as they needed, product does not need to be built in advance. The last step is to seek

‘perfection’ in which the previous four steps are repeated to eliminate the waste completely and only value-added (VA) activities exist in value stream.

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Lean Road Transportation

There are some specific lean concepts tools developed by other researchers to eliminate transportation waste such as Total Overall Vehicle Effectiveness (TOVE) [32], Transportation Value Stream Mapping (TSVM) (Villarreal, 2012) and Seven Transportation Extended Waste (STEWs) (Sternberg et al, 2013) were used to improve the transportation in manufacturing industry. For example, the TOVE and TSVM metrics were combined to improve the transportation in a Mexican convenience store firm, OXXO, and the result was that a total of 56% routing cost was saved after applying lean thinking methodology to the routing operations (Villarreal, 2012).

The research in lean road transportation can be divided into three areas (Villarreal et al, 2016).

These three areas are listed as follows:

(i) From production to transportation waste.

(ii) Lean performance measure for road transportation.

(iii) Improvement of road transport operation.

From Production to Transportation Waste

Some of the researchers such as Guan et al. (2003) and Sternberg et al. (2013), discovered the potential of adapting the seven wastes philosophy from TPS to enhance the operations on the road (Guan et al, 2003; Sternberg et al, 2013). Several new sets of lean transportation tools were developed from the original Toyota’s lean production concept. There are five types of waste exist in transports, which are delays of quality, driver breaks, excess load time, speed losses and fill losses (Guan et al, 2003). Besides that, only five out of seven wastes from TPS are applicable in motor carrier operations and STEWs was derived from Toyota’s original waste concept by replaced the conveyance and inventory waste with resource utilization and uncovered assignments (Sternberg et al, 2013).

Lean Performance Measure for Road Transportation

Continuous improvement is the basis of lean principles. This can be achieved in transportation by the support of certain metrics. Continuous measurement is important to enhance the operations (Dey & Cheffi, 2013). Overall Vehicle Effectiveness (OVE) (Shingo & Dillon, 1989) metric modified from Overall Equipment Effectiveness (OEE) (Nakajima, 1988) metric was used to measure the performance of truck transportation and improve the operation. Later on, OVE was modified further by (Guan et al, 2003) and (Villarreal et al, 2012). The performance factors were grouped into two components, which are time and route efficiencies (Guan et al, 2003). On the other hand, TOVE was developed by modifying the OVE (Villarreal et al, 2012). The different between OVE and TOVE are OVE considers the loading time while TOVE considers the total calendar time and administrative availability element was added.

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Improvement of Road Transport Operation

Although transportation considers as a waste under lean principles, it is a necessary process to deliver the products towards the customer. Under certain circumstance, waste in transportation operations can be addressed by improving the efficiency of the operation (Fugate et al, 2009;

McKinnon, 1999). Nowadays, an efficient transportation operation considered as a value added factors to the customer (Villarreal et al, 2009).

It is proven that by applying the methodology introduced by Hines and Taylor (2000) that consists of four stages in eliminating transport waste [8], helps a Mexican firm saved up to $700000 of capital investment cost and operations cost of $1400000 per year (Villarreal et al, 2009).

3. Problem Statement

Lean principles have been implemented in industry to improve the efficiency and reduce the cost, however, research on application of lean principles and lean metric to eliminate the waste in transportation is rather limited (Villarreal, et al., 2009). Even though there are some others approach to eliminate transportation waste and problems such as mathematical modelling, simulation and operations research, however, the many others doubting the effectiveness of these methods in addressing the real-life transportation problems (Berhan, et al., 2014). This research aims to carry out a case study how integrating lean principle into computer software helps to eliminate transportation waste.

4. Method

4.1 Development of Smart Identification Software System

Proper project planning and continuous literature review were done to identify the flaws that exist in the transportation system of manufacturing plants and to improve it with the support of the developed computer software.

In the programme writing, optimized usage of the transport is considered as waste based on lean principles. This smart waste identification system or lean transportation software is designed by using the Microsoft Visual Studio software and it is developed mainly for Windows platform users.

The programming language used in this software is C Sharp (C#). It is developed to support both 32-bits and 64-bits Microsoft Windows Operating System (OS) devices only and not applicable for other OS devices such as Mac OS, Chrome OS and Linux.

The main function and feature of this software is to help a company to identify the transportation flaws which causes waste and at the same time helps the company to monitor the performance of the company by providing the data on the previous delivery session. The major function of this software is to allow the user to record the data related to transportation operation in a company into the software and store it in the database.

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4.2 Data Collecting

To ensure the software work as what it is designed to do, a case study was conducted in a manufacturing company called ABC Industries (name of the company was changed to protect the privacy of the company). On site data collecting will be perform in the onsite visiting company.

The flow of the transportation operations in the company will be identify. Data and information such as vehicle space usage, travel distance, travel time, loading time and unloading time will be collect and record for analysis and improvement purpose.

4.3 Data Analysis and Evaluation

This stage involves the processing of data and information collected from the onsite company. The analysis process is to be conduct with the support of the computer software. An evaluation report on the achievement and effectiveness of this software system will be generated after the analysis process

5. Results and Discussion

5.1 Lean Transportation Software

The following list is the information data that can be stored into this software:

(i) Customer’s order.

(ii) Transportation records.

(iii) Forecast records.

(iv) Company’s expenses on transportation.

(v) Company’s budgets allocate for transportation.

(vi) Company’s vehicles information.

(vii) Latest fuel cost.

When the data is required, the user can recall the data stored in the database. Analysis and evaluation can be conducted based on the data recorded, the goal of this objective is to reduce the waste exist in the company’s transportation operation such as extra distance travelled, excess time taken and delay in delivery. By referring to the previous record, a company is able to compare the difference between each of the delivery session. For example, when the company wanted to deliver goods from destination A to destination B, the company can refer back to the records in the software whether an identical delivery has been made previously. This provide the company a guideline to plan the most effective route for current delivery session and set a benchmark to evaluate the efficiency of this delivery session

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5.1.1 User Interface

This software is divided into two sections which consist of an upper section and a bottom section as illustrated in Figure 1. Each part consists of several tabs which allow the user to perform different functions. The upper section let user to input different types of data into the software while the bottom section let user to check and search for the data recorded in the software.

Figure 1: User Interface

5.1.2 Upper Section Functions

The upper section of the software consists of seven-tab pages and each tab allows the user to record and input a specific type of data into the software. The name and function of each of the tab pages are described in Table 1 below.

Table 1: Function of upper section’s tab page No Tab Page Name Function

1 Order Record customer's order into database.

2 Transportation Input

Record the transportation information for each delivery session.

3 Forecast Input Input forecast information of a delivery into the software.

4 Expenses Record company's expenses for transportation for a specific period.

5 Budget Record budget allocated for transportation for a specific period.

6 Vehicle Info Record vehicle information that being use for transportation purpose.

7 Fuel Cost Record the latest fuel cost.

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5.1.3 Lower Section Functions

The lower section of the software consists of six-tab pages which allow the user to monitor and search for the data recorded in the database. The name and function of lower section’s tab pages are shown in Table 2.

Table 2: Function of lower section’s tab page

5.1.4 Operation of Software

When data is input into the software through upper section’s tab page, that information will be stored as database of the software. For example, if a set of data is input into the software by using the transportation input tab page, information such as starting point, end point, travelled distance, time taken to travel from starting point to end point, date of delivery, departure time and vehicle type used will be stored into the software database.

This software allow user to search for this set of data through the lower section’s tab page to trace back the record and use it to compare another set of data to compare it within the software whether is there any difference between both set of data such as date of delivery, departure time, travelled distance and time taken. For example, company ABC deliver goods to point A in the same day but different timing by using the same route, there will be a difference in time taken for travelling, based on this comparison data user can identify when is the best timing to deliver the goods to customer that will utilize the least amount of time. This will eventually help the user to eliminate the waste of time spend on deliver and utilize the extra time saved for next delivery so that more delivery trip can be achieved within a day hence improve efficiency.

At the meantime, this set of data will link to other sets of data such as fuel cost to calculated the fuel cost required for each delivery session based on market fuel price and type of vehicle used for the delivery. Form here user is able record the amount of money spent on fuel for a certain period of time for instance within a month. These recorded data able to use to compare with the budget allocated for fuel expenses in company financial planning and provide the user a platform to monitor expenses on fuel and control it by having a proper planning delivery schedule and vehicle type use to ensure it is within budget allocated to avoid over spending as high expenses on fuel always one of the major issue encounter by many company.

No Tab Page Name Function

1 Waiting List Check the order made by customer which have not been delivered out.

2 Transportation Records

Check the data recorded for previous delivery session.

3 Forecast Records Check the forecast data recorded.

4 Maps Allow user to search for information in Google map.

5 Summary Show the summary of transportation records, expenses and budget.

6 Order Check List Check items that contain in an order.

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5.2 Background of ABC Company

ABC Company is a recycle plastic manufacturer and a consultant company for polythene waste.

They specialize in recycle plastic bag other waste, their products include high-density polyethylene (HDPE), polypropylene (PP) and low-density polyethylene (LDPE) resin. Their major customers are mostly from the city center area (the area of study at Kuala Lumpur, capital city of Malaysia).

As the city center is a high population area, it is a busy area and the density of vehicle in this area is very high as well. Traffic congestion happens very often due to the high density of traffic on the road especially during peak or working hours. This cause delivery job become a challenging task as the goods have to be deliver to customer in a limited amount of time, traffic jam will cause delay of the delivery. Besides that, excess time used in a delivery session will increase the delivery cost as well as extra fuel is required to run the vehicle. A case study is conducted to study the transportation system in this company in order to help them identify the flaws and improve the efficiency of the transportation system.

5.3 ABC Company Transportation Data

The actual distance travelled and trip duration information was collected from ABC Company while information on forecast distance and duration were acquired from Google Maps. Point A is the most frequently travelled delivery point for ABC Company. Point B and Point C are also their frequent delivery places; hence, these three points were selected for this study.

Table 3 shows the difference in percentage (%) in terms of distance and duration between ABC Company and Point A.

The difference is automatically calculated by the software based on this formula:

(𝑎𝑐𝑡𝑢𝑎𝑙 − 𝑓𝑜𝑟𝑒𝑐𝑎𝑠𝑡)

𝑎𝑐𝑡𝑢𝑎𝑙 𝑥100%

Table 4 and Table 5 show the difference in percentage (%) in terms of distance and duration between ABC Company and Point B, and ABC Company and Point C, respectively.

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Table 4: Difference between ABC Company and Point B

From ABC to Point B From Point B to ABC

TIME

% difference between actual and forecasted distance

% difference between actual and forecasted time

11:45 AM 0 1.6 0 -6.3

12:15 PM 0 3.1 0 -6.3

12:45 PM 0 0 0 -6.3

1:15 PM 0 3.1 0 -1.6

1:45 PM 0 1.6 0 -1.6

2:15 PM 0 3.1 0 -3.1

Day 1 ^{Day 2}

From ABC to Point A From Point A to ABC From ABC to Point A From Point A to ABC

TIME

% difference between actual and forecaste d time

% difference between actual and forecaste d distance

% difference between actual and forecaste d time

8:15AM 0.00 -6.05 -10.64 -2.56 0.00 11.80 -4.90 -2.10

8:45AM 0.00 -3.98 -10.64 -2.56 0.00 17.60 -4.90 0.00

9:15AM 0.00 -3.98 -10.64 -2.56 0.00 15.70 -4.90 0.00

9:45AM 0.00 -3.98 -10.64 -2.56 -2.20 11.80 -4.90 0.00

10:15AM 0.00 -3.98 -8.51 -1.28 0.00 11.80 -4.90 0.00

10:45AM 0.00 2.13 -8.51 4.17 0.00 9.80 -0.90 0.00

11:15 AM 0.00 -2.13 -8.78 0.00 0.00 9.80 -0.90 2.10

11:45 AM 0.00 -2.13 -8.78 0.00 0.00 11.80 3.20 -8.30

12:15 PM 0.00 0.00 0.00 2.08 0.00 7.80 3.20 -6.30

12:45 PM 0.00 4.26 0.00 6.25 0.00 11.80 3.20 -6.30

1:15 PM 0.00 6.38 0.00 8.33 0.00 13.70 -4.90 2.10

1:45 PM 0.00 6.38 -8.78 8.33 0.00 11.80 -4.90 8.30

2:15 PM 0.00 4.26 -8.78 6.25 0.00 11.80 3.20 6.30

2:45 PM 0.00 2.13 -25.71 4.17 0.00 11.80 -4.90 2.10

3:15 PM 0.00 4.26 0.00 6.25 0.00 11.80 3.20 4.20

3:45 PM 0.00 0.00 0.00 2.08 0.00 9.80 3.20 4.20

4:15 PM 0.00 2.13 -7.21 4.17 -2.90 9.80 3.20 4.20

4:45 PM -2.23 4.26 -3.76 6.25 0.00 2.00 3.20 -2.10

5:15 PM -2.23 -8.51 -0.63 -6.25 0.00 -3.90 -3.50 -10.40

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2:45 PM 0 1.6 0 -3.1

3:15 PM 0 3.1 0 -4.7

3:45 PM 0 3.1 0 -3.1

4:15 PM 0 3.1 0 -3.1

4:45 PM 0 1.6 0 -6.3

5:15 PM 0 0 -4.1 -14.1

Table 5: Difference between ABC Company and Point C

From ABC to Point C From Point C to ABC

TIME

8:15AM -14.3 16.1 -10.1 26.5

8:45AM 1.5 19.6 -10.1 26.5

9:15AM 0 17.9 0 29.4

9:45AM 0 16.1 0 23.5

10:15AM 1.2 16.1 -5.4 26.5

10:45AM 1.2 14.3 -6.8 26.5

11:15 AM 0 17.9 -5.4 29.4

11:45 AM 0 14.3 0 22.1

12:15 PM 0 14.3 0 20.6

12:45 PM 1.2 14.3 0 22.1

1:15 PM 0 17.9 0 32.4

1:45 PM 0 19.6 0 41.2

2:15 PM 0 19.6 0 36.8

2:45 PM 0 17.9 0 35.3

3:15 PM -10.4 16.1 0 36.8

3:45 PM -10.4 16.1 0 36.8

4:15 PM 1.2 12.5 0 36.8

4:45 PM -1.5 5.4 0 33.8

5:15 PM -1.5 -3.6 -6.8 25

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5.4 Analysis of the Transportation Data

The actual data was compared with the forecast data at a specific time to check their accuracy and reliability. Based on the observation from the readings obtained, it could be concluded that the forecast data obtained from Google Maps are similar to the real-world data recorded from the company. The difference percentage is under 30% and acceptable as per Rodriguez et al.

(Rodriguez et al, 2018). Therefore, the forecast data can be used to represent the real-world data.

Hence, with this software, the company can (i) use the forecast data from Google Map to build their own database, based on their desired time and day; (ii) record as much actual data as they operate to accumulate more real-world data. Then, the software will automatically generate the difference between actual and forecast data once there are keyed in. A positive value means the actual distance or time is larger than the forecasted value, whilst a negative value represents the forecasted distance is longer or the forecasted time takes longer. This smart system will assist in accumulating big data for the company’s delivery records in terms of distance and duration.

The history of a certain delivery can be recalled conveniently by using the database created by the software. With the help of the software, flaws that exist in the transportation system of manufacturing industry can be identified easily. For example, if certain companies already have the database of their delivery information, they will be able to choose a more suitable time for delivery that reduces excess or unnecessary delivery time. Excess delivery time will directly affect the transportation cost as more fuel may be required to run the vehicle or the increase of driver’s salary if an overtime rate incurred. Indirectly, this may also impose a negative impact to the customer at Point A, if the delivery is delayed. Delivering on time will gain customer’s trust.

Besides, when one delivery is delayed, it may affect the next delivery on schedule. As it snowballed, it will affect the inventories as goods are not cleared, and eventually the whole production and operation chain. Therefore, time is money.

From the table, there are data where the distance difference between actual and forecast is 0%

while the time at the corresponding measured time has a percentage of difference. This may due to traffic congestions or speed of the driver. With this information, it helps the company to decide the ideal time to do a delivery. For example, by referring to Table 4, the delivery time from ABC Company to Point B can be reduced by 3.1% if the delivery is done around 2:15PM instead of 12:45PM. As there is no other delivery within that day, it is possible for them to reschedule the delivery time to 2:15PM. Moreover, the delivery in the evening such as 5pm may be avoided altogether as the data shows a larger difference and this may be due to traffic congestion during rush hours. Time management is essential to increase a company’s productivity. This database will be useful to check on the pattern of traffic according to seasons as well, such as low or peak seasons, festive seasons, holidays or yearend seasons.

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Currently, there are other smart phone applications like Waze or Google Map that shows the estimated time and distance required. These applications however, will only be able to give information when that particular time arrives. This is because Waze and Google Map are designed to track the real time location with Global Positioning System (GPS) to give the current information only (Jeske, 2013). The new developed software, however, can give a whole scenario and time choices for a company to plan ahead their delivery schedule. Having a proper delivery schedule is important as the company can save time and cost.

6. Conclusion

The research has developed a smart waste identification lean system to identify the waste and improve the transportation system. Case study was adopted to test the system in ABC Company.

The system is able to help the company to accurately detect the extra time taken in one of the delivery sessions. The delivery time can be improved based on the forecasted and analysed data.

This system will help in reducing the wastage of resources and at the meantime improving the transportation operations of the company. This can be achieved by reducing any unnecessary operation or activities in transportation that being identified by the software. Moreover, this system will also be useful other industries that requires logistics or delivery of material goods such as in the construction industry.

Certain limitations need to be considered in this study. This scope of the research only focuses on improving the transportation system by reducing the waste in manufacturing industry. It may not be applicable to transport goods in other industry such as chemical substance. The case study was also conducted based on one manufacturing company, hence, the data and result acquired may not be able to represent the whole manufacturing industry in Malaysia. Furthermore, some of the factors and unforeseen circumstances that will affect the outcome are not consider in this system such as weight of the vehicle and bad weather. However, it could be used as a reference for future implementation. Furthermore, the software can be improved by including different routes to the specific destination, or having few destinations in one delivery to save time and cost.

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7. Acknowledgement

Through this acknowledgement, we would like to take this opportunity to express our gratitude to who had contributed and supported us throughout the whole research project that leads us to successful completion of this project.

First of all, we would like to extend our thanks Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia and School of Design and the Built Environment, Curtin University, Perth, Australia as they provided us a platform to undertake and complete this project.

Last but not least, we would also like to thank Company ABC for allowing us to carry out an onsite case study at the company and spending their precious time to help us collect the data that means a lot to this study.

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