Mapping of Material Transportation Routes in Production for Optical Measurement Instrument With the Purpose of Improving
Efficiency
Clara Danielsson
Mechanical Engineering, master's level 2020
Luleå University of Technology
Department of Engineering Sciences and Mathematics
Acknowledgements
This report is the result of a 20 weeks long master thesis project corresponding 30 ECTS credits carried out during the fall of 2019 at Trimble AB through AFRY consulting. The project concludes my studies towards a Master of Science in mechanical engineering, spe- cialised towards production at Luleå Tekniska Universitet.
I would like to thank everyone at Trimble AB who have taken the time during the fall to help me and answer all my questions and supported me through the project. This es- pecially goes for my supervisors Linn Olsen from operations and Johan Öhlund at product development who have shown great interest in the project and not just in the results.
I also want to thank my supervisor at AFRY, Johan Rössner, who from the very begin- ning asked what I needed from AFRY in order to succeed with the project.
Finally I want to give a big thank you to Jesper Sundqvist, my supervisor and examiner at LTU for always answering my questions quickly and taking the time for me during the fall.
Stockholm, January 20, 2020
Abstract
Trimble AB is a part of the international group Trimble Ltd. Trimble Ltd. was founded in 1978 and has development units, factories and retailers all over the world.
Trimble AB develop and manufacture high technical and electro-optical range finders and angular measuring instruments. These instruments are called ’total stations’ and are primar- ily intended for surveying, the construction industry and as control system for construction equipment. This master thesis project has been conducted at Trimble AB’s site in Danderyd, Stockholm.
The purpose of the master thesis have been to examine potential efficiency improvements of internal material transport since Trimble aims to increase production significantly, with- out increasing the need for more staff.
Today, all transportation from the warehouse, between the assembly and manufacturing de- partments is conducted manually where operators either carry or transport a material cart.
The transport routes are long and sometimes between floors. Since the instruments often have to be adjusted, components are changed, they are re-calibrated etc., the flow in pro- duction is complicated and there is no knowledge of how manual transports are handled today.
This project have conducted a thorough mapping of the current state for one of the instru- ments Trimble manufacture, model S7. This in order to gain knowledge of how transportation are connected and handled in production today. The mapping of transportations resulted in identified problem areas as well as a method standard for mapping that can be applied on the entire flow. The identified problem areas could be summarized as a lack of standard regarding handling of transportation for Trimble, which in turn affects the efficiency of the manual transportations.
The project and the work done have resulted in various suggestions for solutions for Trimble regarding how they can standardize material transport, all of which will lead to more efficient transport in the future. Both short term and long term suggestions for how implementation should be handled are presented along with what areas Trimble should focus on in the first step. Standardisation acts as a basis for allowing Trimble to work with continuous improve- ments and solutions require low investments from Trimble today and enables them to conduct a more thorough and deeper mapping for future projects regarding efficiency.
Keywords: Standardisation, continuous improvements, deviations, waste, efficiency
Sammanfattning
Trimble AB ingår i den internationella koncernen Trimble Ltd som är noterad på Nasdaq- börsen i USA. Koncernen grundandes 1978 och har utvecklingsenheter, fabriker och åter- försäljare över hela världen.
Trimble AB utvecklar och tillverkar högteknologiska elektrooptiska avståndsmätare och vinkel- mätningsinstrument, så kallade totalstationer, avsedda främst för lantmäteri, byggnads- och anläggningsindustrin samt styrsystem för entreprenadmaskiner. Det här examensarbetet har utförts på Trimble ABs enhet i Danderyd, Stockholm.
Syftet med examensarbetet har varit att undersöka potentiella effektiviseringsmöjligheter av de interna materialtransporterna då Trimble har målet att öka produktionen betydligt, utan att öka personalbehovet.
I dagsläget sker all transport från lager, mellan montering och tillverkningsavdelningarna manuellt där personal bär eller använder vagnar för att förflytta material. Det är långa trans- portvägar och sker ibland mellan två plan. Då instrumenten många gånger måste justeras, komponenter bytas ut, kalibreras om etc., är flödet i produktionen komplicerat och i dagsläget saknas det kunskap om hur de manuella transporterna hanteras.
I projektet har en noggrann kartläggning av nuläget genomförts för en av modellerna av instrument Trimble tillverkar, modell S7. Detta för att skapa en bild av hur transporter hänger ihop och fungerar i produktionen. Kartläggningen av transporter resulterade i identi- fierade problemområden samt en utvecklad metodstandard för kartläggning som är applicer- bar på hela flödet. De identifierade problemområdena kunde sammanfattas i en avsaknad av standard gällande hantering av transporter för Trimble vilket påverkar effektiviteten av de manuella transporterna.
Projektet och arbetet har resulterat i olika förslag på lösningar för Trimble hur de kan stan- dardisera materialtransporter som alla kommer leda till effektivare transporter i framtiden.
Både kortsiktiga och långsiktiga förslag på hur implementering bör ske har presenterats samt vilka områden Trimble bör fokusera på i första steget. Standardisering agerar som en grund för att låta Trimble arbeta med ständiga förbättringar och lösningarna kräver låga investeringar av Trimble i nuläget samt gör det möjligt för Trimble att göra noggrannare och djupare kartläggningar för framtida effektiviseringsprojekt.
Nyckelord: Standardisering, ständiga förbättringar, avvikelser, slöseri, effektivisering
Contents
1 Introduction 1
1.1 Company Introduction . . . . 1
1.2 Background . . . . 1
1.3 Objective and goals . . . . 2
1.4 Scope . . . . 2
2 Theory 4 2.1 Lean Production . . . . 4
2.1.1 Standardisation . . . . 5
2.1.2 Continuous Improvements . . . . 6
2.1.3 Waste . . . . 6
2.1.4 Spaghetti Chart . . . . 7
2.2 Logistics . . . . 8
2.3 Automated Guided Vehicles . . . . 9
3 Methodology 10 3.1 Project Planning . . . . 10
3.1.1 Time Plan and Milestones . . . . 11
3.1.2 Research Approach . . . . 11
3.1.3 Literature Study . . . . 11
3.2 Mapping and Analysing . . . . 12
3.2.1 Observations . . . . 12
3.2.2 Interviews . . . . 13
3.2.3 Internal Database . . . . 14
3.3 Identifying Needs and Requirements . . . . 14
3.4 Generating Ideas . . . . 14
3.5 Concept Development . . . . 15
3.6 Implementation . . . . 15
3.7 Reliability and Validity . . . . 15
4 Results of Empirical Execution 17 4.1 The S7 model . . . . 17
4.2 Mapping of Material Flow . . . . 18
4.3 Mapping of Transportation . . . . 23
4.3.1 Optics . . . . 23
4.3.2 Accessories . . . . 26
4.3.3 EDM . . . . 27
4.3.4 Telescope Assembly Line . . . . 28
4.4 Results of Summarized Mapping . . . . 29
4.4.1 Analysis of Mapping . . . . 30
4.5 Interviews . . . . 31
4.5.1 Interview Summary . . . . 32
4.5.2 Interview Analysis . . . . 32
4.6 Problems Identified . . . . 33
4.6.1 Lack of Standardisation . . . . 33
4.6.2 Lack of Knowledge About Processes . . . . 34
4.6.3 Unnecessary Movements . . . . 34
4.6.4 Extra Transportation . . . . 35
4.7 Identified Problems Summarized . . . . 35
5 Results and Analysis 36 5.1 Solutions for Identified Improvement Areas . . . . 36
5.1.1 Method Standard for Mapping . . . . 36
5.1.2 Method Standard for Transporting Material . . . . 37
5.1.3 Replacing Manual Transportations . . . . 39
5.2 Result Analysis . . . . 41
6 Discussion 42 6.1 Limitations and Scope . . . . 42
6.2 Mapping . . . . 43
6.2.1 Standard Method Mapping . . . . 43
6.2.2 Standard Method Transporting Material . . . . 44
6.2.3 Replacing Manual Transportations . . . . 45
6.3 Handling of Implementation . . . . 45
6.4 Reliability and Validity . . . . 46
7 Conclusions 48 7.1 Research Questions . . . . 48
7.2 Future Work . . . . 50
7.2.1 Short Term Implementations . . . . 50
7.2.2 Long Term Implementations . . . . 51
7.3 Goal Fulfillment . . . . 52
Appendices i
A Gantt Chart i
B Interview Template ii
C Data table for visual chart of Subbasembly 1 iii
D Data table for visual chart of Subbasembly 6 iv
Abbreviations
AGV Automated Guided Vehicle BOM Bill of Materials
LT U Luleå university of Technology T P S Toyota Production System T T S Trimble Tracking System R&D Research and Development P U Product Development
1 Introduction
This chapter gives an insight into the company Trimble AB and the site in Danderyd, provides appropriate background to the problem, formulates objectives and goals and present the scope for the project.
This thesis project has been conducted at Trimble AB in Danderyd in collaboration with AFRY in Solna, where AFRY provides the master thesis student as a consultant. The client is Trimble AB and the owner of the project is the Research and Development Department (R&D) at Trimble AB. This means the project has been able to use AFRY’s contact network and their knowledge and expertise to gain support during the projects progress.
1.1 Company Introduction
Trimble AB is a part of the international group Trimble Ltd which was founded in 1978 and have about 11,000 employees worldwide. Trimble AB has a site located in Danderyd, Sweden. This site is part of the Geospatial Branch of Trimble Ltd. that develops and manu- factures high technical and electro-optical range finders and angular measuring instruments, so called ’total stations’. The instruments are primarily intended for surveying, the construc- tion industry and as control system for construction equipment. Besides that Trimble AB also manufactures 3D scanners for spatial imaging applications. A majority of Trimble AB products are exported. The unit at Danderyd have about 300 employees.
At the R&D department, one group is the Product Development group (PU). They are re- sponsible for developing new products and solutions and to ensure they can be implemented in the current production. The PU department are owners of this master thesis project.
1.2 Background
The manufacturing process of instruments at the site in Danderyd currently consists of as- sembly, calibration and testing. All this is done manually by operators who also handle the internal transportation of materials between manufacturing stations and departments. The instruments consists of subassemblies, which in turn consist of different components that are assembled in different parts of the factory before being delivered to final assembly. This creates a complicated flow of material within the production flow and involve a lot of man- ufacturing departments. Today there is no clear image of what the transport routes for the material looks like or how much time is spent on internal material transport.
Trimble believes that the travel distance for the components in an instrument and the time operators spend on transporting materials through the factory can be streamlined, thus re- ducing waste and creating more efficient internal transportation.
Trimble AB aims to increase production significantly without increasing the need for more personnel. One suggestion is to investigate how profitable it will be to increase efficiency for material transportations.
1.3 Objective and goals
The thesis project aims to map the current flow of material transportations in production, measure time and distance of said transports and identify improvement potential. The goal of the project is thus to create suggestions on how Trimble can create more efficient trans- portations.
To map the current flow, an appropriate method will first be determined through a literature study. Then a current state analysis will be performed with identified and developed method for mapping and analysing. Based on the results of the analysis suggestions for improvement will be made. The purpose of the mapping and analysis is to identify how Trimble AB will be able to make transportation of materials in production more efficient. For this project, 5 research questions are formulated to ensure that project objective is fulfilled. These questions are:
1. How are internal material transportations in production handled today?
2. What is the best way to map the transportations of material in production?
3. How can material transportations become more efficient?
4. How will Trimble be able to implement made suggestions for improvement?
5. What are the possible effects of said improvements for Trimble?
By answering the stated research questions above, the purpose of the project will be fulfilled and the goals will be reached.
1.4 Scope
To ensure that the project is performed as accurate as possible and stays within the appropri- ate scope, potential problems are identified and analysed. Delimitations are made together with supervisors both at Trimble AB, AFRY and with involved staff at Trimble. Since the manufacturing process for the products produced at Trimble is complicated and differs a lot for each individual product, there is a risk that the flow becomes too complicated to map correctly during the 20 weeks designated for the master thesis if all the different products are to be analysed. The warehouse where packaging and shipping takes place have their own system for handling the instrument and if instruments are to be tracked and their routes through the warehouse mapped the scope starts to creep which might make suggestions for improvement complicated.
Finally, there are subassemblies to all the different products and for some of the instruments there are up to almost one hundred different models. Mapping the routes for all the sub- assemblies without being able to make simplifications will be very time consuming and create large amount of data which cannot be analysed in this projects timeline. Based on the project description, the time frame, and identified potential problems, the following delimitations are made:
• The flow of production for one of the products, S7, is mapped.
• The mapped area excludes the main storage where packaging and shipping takes place.
• One branch of subassemblies will be mapped from start components to finished instru- ment.
Together with staff at Trimble responsible for the daily production, it is deemed appropriate that the subassembly that should be targeted is the telescope of the S7 instrument. The telescope has its own manufacturing and assembly line and acts as a subcontractor to the main assembly line for the S7 instrument. The telescope contains a lot of components manufactured at the different departments of manufacturing, making sure the mapping will cover enough area.
2 Theory
The following chapter presents the theories used in this thesis report. The subsections will present different methods practiced in Lean production, material planning and material con- trol.The literature review is based on research found in scientific articles and books covering the relevant subject.
2.1 Lean Production
Lean production is a term first introduced by Womack, Jones and Roos (1990) and refers to the Toyota Production System known as TPS. Lean is used differently in all organisations, for some companies it means using certain "Lean" methods to streamline processes and for other organisations it is a strategy that includes the entire organisation (Peterson et al., 2015). Toyota, who came up with the production system, states that Lean production is a refined system where all parts work together as a whole, where support and encouragement to search for continuous improvements for the processes is key (Liker, 2009). Liker (2009) further states that TPS can be divided into four categories (Philosophy, Processes, Partners and Problem solving) that consists of 14 principles. The four categories and their principles is sometimes referred to as the 4P pyramid. The first P is philosophy, the foundation of the Lean principles which includes the first principle and all other principles are based of this.
The second P represents process and waste elimination, the third P stands for people and partners and includes respect and teamwork and the top of the pyramid is problem solv- ing, meaning fully working with continuous improvements (Liker, 2009). The 4P pyramid is shown in Figure 1 and describes each step in the pyramid with their associated principles.
Figure 1: 4P Pyramid from Toyota Production System.
Womack and Jones (1990) states that a Lean business follows a five step process. First customer value is identified, then the value stream is defined, after that an even flow is created, pull manufacturing established and finally the business or organisation will strive for perfection.
To become a Lean manufacturer a way of thinking is required that not only focuses on making the product continuously flow through the value adding processes and creating a pull system that matches the customer need. It also requires a culture within the organisation that strives for continuous improvements (Liker, 2009).
2.1.1 Standardisation
Standardisations creates the foundation for an organization to work with continuous improve- ments, since to improve the current situation, an initial way of how processes work or tasks are performed needs to be determined (Peterson et al., 2015). The concept of standardisa- tion describes the right now known and agreed of way of performing an operation or task (Segerstedt, 2008). Since the Lean principles form the basis for a companys development towards Lean, those principles in turn provide guidance towards concrete solutions. Peterson et al. (2015) describes the developed solutions agreed upon and formalized as the standard itself.
The agreed upon standard should be central for the company and the starting point for all work and Liker (2009) states that when an organization has a standard in place, it helps discoverer deviations for a process or task within the organization.
When a task is performed that differs from the standard, it is considered a deviation, which explains how standardisation can help discover abnormalities within the company and thus helping in reducing waste and contributing to continuous improvements (Peterson et al., 2015).
According to Peterson et al.(2015) standardisation is important on all levels in an organ- isation and specifically mentions three areas
• Flow Level
• Process Level
• Workplace Level
What needs to be standardized on these levels are first and foremost actions that affect the organisations different stakeholders such as customers, suppliers, coworkers, owners etc.
For flow level, an example of a standard could be the size of bufferts between stations or batch sizes, where a process standard describes how a certain action or operations should be performed. With workplace standards, Peterson et al.(2015) refers to agreement on how the workplace should be configurated, for example where should materiel be stored, documents saved etc.
The important difference between the different levels of standard is who is responsible for creating and keeping said standard updated (Segerstedt, 2008). It is important that the responsibility lies with the employees who are concerned by the standard since they will be working with the action/operation/process/etc. and it will not only race the incentive of using said standard but the relevance will be higher (Liker, 2009).
2.1.2 Continuous Improvements
Continuous improvements is a theory that originates from Lean philosophy and TPS, called Kaizen in Japanese, and is an important part of the TPS pyramid (Liker, 2009). With con- tinuous improvements TPS claims that improvements are to be made in everyday operations and in small controlled steps. Meaning that change in an organization to improve the cur- rent situation does not always have to be a project that requires a lot of resources, but can sometimes be a small change in the daily operations for example (Peterson et al., 2015).
This will not necessarily have a great effect on the results but in return does not require a lot of effort from the organization.
Working with continuous improvements in the organization is a part of the Lean strategy and is about striving for perfection through continuously working on improving the organization (Peterson et al., 2015). Since Lean is something a company or organization always have to work with, continuous improvements is a never ending process. Since perfection within the organization is never achieved, continuous improvements it thus an absolute philosophy that strives for perfection and maintains Lean (Modig & Åhlström, 2017).
Well performing organizations have managed to establish continuous improvements within their entire organization, which is a corner stone in order to succeed with Lean(Galli, 2005).
To use deviations as a fuel for improvement has been discovered to be successful since when the people working within the organization are a part of the process of continuous improve- ment they are motivated to identify deviations and to eliminate discovered deviations (Pe- terson et al., 2015).
2.1.3 Waste
Waste, or Muda in Japanese, is a term used in Lean to describe activities that adds no value to a process for any of the stakeholders (Liker, 2009). Waste elimination is a cornerstone in creating continuous improvements since it helps to discover deviations that are not part of
the standardized process. In Lean theory, there are 7+1 wastes:
• Overproduction
• Wait
• Transport
• Extra processing
• Inventories
• Motion
• Defects
• Unused skills
They are called the 7+1 wastes since the first seven originate from TPS and the eight one is to highlight how much it affects the organization when the people involved in processes are able to contribute with their knowledge (Peterson et al., 2015). By dividing resources in "value adding" part and a "non-value adding" part, Lean theory states that focus can be made on eliminating the non-value adding part, i.e. the wastes, in order to free resources and allocate them to more value adding processes (Segerstedt, 2008). The two most interesting types of waste for this project is transport and motion.
Internal transport is considered a pure waste for organizations and thus an important question to ask is why transportation is necessary for the organization or the specific process(Peterson et al., 2015). Sometimes organization focus on replacing the type of transport, but to use trucks, both manual and automated, in order to perform the transport does not entail a transport rationalization in general but instead only rationalize the work around the trans- port. Thus according to Peterson (2015) the focus should be on eliminating the need for transportation.
Motion is described as a movement that does not contribute to add value to the finished product, this can be for example walking long distances in a factory, searching for tools or material or performing unnecessary tasks (Peterson et al., 2015).
2.1.4 Spaghetti Chart
As stated in previous section, transportation within production is considered a waste within the Lean philosophy (Liker, 2009). In order to reduce internal transportation for an organi- zation a Spaghetti chart can be made to get an overview of the distance the transportation covers.
Spaghetti charts aim to visualize transport and movement within the processes and flow of production, this can mean both transportation of material, equipment and products as well as transportation of humans and information (Peterson et al., 2015). The visual chart is created from a layout of the facility where physical movements are closely traced through
detect deviations and eliminate unnecessary movements. The Figure below presents an ex- ample of an Spaghetti Chart for a manufacturing process where each line represent a type of transportation.
Figure 2: Example of a spaghetti chart for product flows along the value stream.
2.2 Logistics
The role of logistics is to transport the right material in the right quantities with the right quality to the right place and in the right time (Sulírová, Závodská, Rakyta, & Pelantová, 2017). This requires a lot of planning and different methods can be applied to increase the efficiency and to ensure the quality is high enough. Lean methods presented above are inte- grated in the planning and the flow of the material can be analysed for further improvement.
Sulírová (2017) explains that the effort made by companies to shorten the lead time of their manufacturing can be achieved by applying modern production techniques, creating more flexible transportation and handling system and by reducing the inventories.
Segerstedt (2008) states that the term logistic has different meaning depending on who you ask but that it can be summarized as the strive for an efficient flow, weather it is a production flow, organisation flow or transportation flow.
When discussing logistics for an organization, three different chains can be distinguished and affect the organization differently, supply chain, logistics chain and transport chain (Lums- den, Stefansson, & Woxenius, 2005).
Supply Chain
Focuses on a consumer product and describes the activities, stakeholders and resources re- quired from raw material to commodity that is available for the consumer.
Logistics Chain
Focuses on an item number and entails form the item number is created until it dissolves, either by becoming a part of a parent article or divided into several new articles.
Transport Chain
Focuses on a consignment and includes transport, physical handling and activities directly re- lated to transport such as packaging, transportation planning, unloading and receiving.
2.3 Automated Guided Vehicles
When material or objects are transported through a factory it can either be manual or au- tomated and to facilitate transportation of resources material trucks or loaders can be used.
The automated versions are called Automated Guided Vehicles (AGV’s) and is a portable robot designed to carry a load and transport itself by using different type of methods (Bell- gran & Säfsten, 2005).
By implementing AGV’s physical automation of the factory is made. Physical automation can be defined as technologies replaces manual labour to perform a task (Fast-Berglund &
Mattsson, 2017). The other automation is cognitive, meaning an action or situation is auto- mated and the response that happens internally within a system is automated.
There are different types of AGV’s and today there are options for more or less any type of organization with different functions and most solutions can be integrated with the orga- nizations internal systems, meaning a solution can be both physical and cognitive, raising the complexity of the automation solution, depending on the purpose of the organization (Fast-Berglund & Mattsson, 2017).
3 Methodology
For this chapter, the chosen methodology used in the project is presented with associated the- ory that supports the methods. The classic project circle with its eight phases acts as a base for the project bearing in mind that the final phases are not followed through. The phases and how they are applied and adapted in this project are described below.
To ensure the project is executed in a structured and methodical manner a model for the project was identified. For this master thesis project the project circle from Johansson and Renhagen (1995) was chosen. The circle contains eight phases:
1. Planning
2. Mapping and analysing
3. Identifying needs and requirements 4. Generating ideas
5. Evaluate and choose alternative 6. Concept development
7. Implementation
8. Follow up and evaluation
For this project, phase 5 is merged with phase 4. This is done since the ideas generated for this project were continuously evaluated throughout the generating process which will be explained in section 3.4
3.1 Project Planning
The first phase contains the planning of the project together with a literature study used for the theoretical framework. This is to create a structure for the project and to distribute resources such as time to ensure the project reaches its goals. Even though the project is an iterative process and the participant is one person with different supervisors it is important to structure the work from the beginning. This will facilitate the different phases and should problems arise, there will be a clear overview on how problems should be handled (Tonnquist, 2010).
3.1.1 Time Plan and Milestones
To be able to carry out the project and get an overview of the purpose and aim, milestones were identified and based on those milestones a time plan in the form of a Gantt chart was created and is presented in Appendix A. The time plan was divided into important milestones and phases for the project since it is the most visual tool that shows the course of the project (Tonnquist, 2010). Together with the time plan a project plan is also presented, this was done early on in the project to ensure the appropriate research approach, scope, milestones and time plan according to the theory was set in consultation with supervisors at both Trimble and LTU. Even though the project plan was set, it is an iterative document that could change as the project proceeded if deemed necessary.
3.1.2 Research Approach
To clarify how the research questions will be answered, a research approach needed to be decided on. Research approaches can be be divided into two fields, inductive and deduc- tive (Saunders, Lewis, & Thornhill, 2009). According to Blackstone (2009) when taking an inductive research approach, data is used to develop a theory and the problem is moved from specific questions to a general solution while a deductive approach is the other way around, where it starts with a theory and then through testing of data proves or disproves the theory. The project aimed to investigate current state and based on collected data create a solution for improvements. Besides this qualitative research takes an inductive approach to data analysis and interpret findings with the help of appropriate theory (Borrego, Dou- glas, & Amelink, 2009). Thus the research approach chosen was an inductive and qualitative research method.
3.1.3 Literature Study
To be able to identify an appropriate method for mapping the flow of the material, a lit- erature study was conducted so that the created method is based on reliable theory. The research questions presented in the introduction acted as support for the literature study and prevented potential scope creep. The literature study is the first step after planning is done so that the next milestone and phase, current state analysis, will be based on solid scientific methods and theories. The main source of information for the study was literature from previous courses at Luleå University of Technology, scientific papers on the subjects logistics, material flow analysis, Lean production and automation techniques together with previous master thesis reports. For the articles, databases like Google Scholar and Scopus were used and previous master thesis reports are from Diva Portal.
3.2 Mapping and Analysing
For phase two, mapping and analysing, a current state analysis was conducted. To be able to map material transportations in production, an appropriate method needed to be estab- lished. The method developed will become a standard of "best practice" for Trimble and used for further mapping of the material flow that is outside of the scope set for this project.
The method was developed through the performed current state analysis and the mapping.
The analysis made was based on collected data. The data gathered was in the form of obser- vations, interviews and information from internal databases and systems at Trimble. For this project it was through the architectural structure of the telescope collected from the database Agile. Agile is Trimbles internal database containing all instruments and subassemblies for Trimbles products. The collected data is analysed and presented along with the results of the current state analysis.
Data can be divided into two classes, qualitative and quantitative (Saunders et al., 2009).
Qualitative data focuses on the diversity to describe patterns and perceptions, where quan- titative data is measurable and has defined variables(Bohgard, 2008). For this project both qualitative and quantitative data has been collected together with a combination of the two classification types.
Methods used for collecting data and if the classification is qualitative, quantitative or a combination of the two is presented in Table 1 below.
Table 1: Data and Classification Type
Method Classification
Observations Qualitative Interviews Qualitative Internal
Database
Combination
The data from the internal database Agile is classified as a combination since it is quanti- tative in the form that it is measurable and has clear variables, i.e. where components are manufactured, which subassembly they are a part of etc. but it is also qualitative since it can be analysed and interpreted by the person collection or analysing the data.
3.2.1 Observations
Observations for this project were mainly made in the form of Go and See, or, Genchi Gen- butsu in Japanese. This is one of Toyotas principles and according to Liker (2009) is one of the key principles and what made TPS so successful. The principle is based on the observer making their observations in person to fully understand the process or situation they are
examining, hence called Go and See.
Since it was important to gain a deep understanding of how material is transported between stations and departments of manufacturing to be able to develop a method for mapping the routes in the future, a lot of emphasis was put on observations early on.
The principle Genchi Genbutsu was applied during the current state analysis, where the ob- server made several observations in the production area at Trimble by following the material and observing the transportation routes made from warehouse to manufacturing department for selected components.
By following the material transportations without interfering, the observations where non- participant since the observer didn’t interfere with the observed operator and therefore could be classed as objective observations (Bell, 2006). The non-participant observations were complemented with what Tjora (2012) refers to as interactive observations where the ob- server interacts with the observed people if the need arises during the observations. This to make sure the observer had full understanding of the process and to minimize misinterpreta- tions. The routes for the material transportations were documented first during observations through notes and photography and then notes were transcribed after observations to make sure documentation was made correctly.
3.2.2 Interviews
Interviews are a subjective and qualitative way of recording people’s opinions on a subject (Bohgard, 2008). This makes interviews useful for qualitative research methods since the data collected can easily be analysed further.
There are different types of interviews according to Bohgard (2008), mainly three categories:
structured, unstructured and semi-structured interviews. Depending on the purpose of the interview, different types can be used, for this project both unstructured and semi-structured interviews were made. Tjora (2012) says that unstructured interviews are suitable for when the interviewer lacks full understanding of the problem at hand. By asking open questions the interviewer can steer the questions depending on the answers and thus making sure the interview covers relevant material. Semi-structured interviews are a mix between structured and unstructured interviews and implies that the interviewer has a template for what areas or subjects are going to be addressed, but can choose the order of the questions and ask follow-up questions (Bohgard, 2008).
During the start-up face of the project, unstructured interviews were held to help create a broader understanding of the current state and not to analyse the answers further. Later on in the project, when the problem at hand was set, semi-structured interviews were held and the results analysed and compared to the results of the mapping of the current state, to find similarities or detect deviations. The semi-structured interviews were based of a template that was developed in consultation with supervisors, the template made room for follow-up questions and can be seen in Appendix B.
3.2.3 Internal Database
To be able to develop a standard method for mapping the flow of material for Trimble, rel- evant data from internal databases was necessary. Data collection in this project, as stated earlier in this chapter, has been made through observations, interviews but mainly from Trimbles internal database for instrument and their components, Agile. From Agile, the Bill of Materials (BOM) for the telescope of the S7 instrument was analysed, the BOM contains all the subassemblies and what components those subassemblies are made of and in what department they are manufactured.
The purpose with the data has been to identify where material is transported within the factory, where components are assembled into larger subassemblies and how those subassem- blies are transported between different departments and assembly stations. By analysing the BOM and sorting the components into different categories, depending on department of manufacturing, subassembly etc. the route of transport could be mapped.
3.3 Identifying Needs and Requirements
The third phase meant identifying needs and requirements. While this is the third phase in the circle, for this project it was done in two segments. First, based on the results of the current state analysis, needs to be able to generate ideas for improving the current state were identified. Those needs were translated into requirements that was based on both interviews but also on observations made during the mapping process.
When the project entered the phase where final concepts were developed, new requirements were identified from unstructured interviews with operators and material handlers simultane- ously while the mapping was conducted. Tasks and actions performed by material handlers during transportations were documented and follow-up questions asked to understand the motivation behind each task and move. The result was documented and compiled in a new requirement specification. The purpose of this was to identify requirements pertaining one of the solutions and to investigate if the goal of the project was reached with this solution.
3.4 Generating Ideas
For this project, generating ideas means identifying possible solutions for improvements. The previous phase had uncovered the root cause of the current problems and thus, the theories and methods identified during the literature study could act as a base for identifying possible solutions.
As stated in the first section of this chapter, this phase was merged together with the phase Evaluate and choose alternative since the generated solutions were continuously evaluated throughout the generating process.
Since it became clear early on in the process that the solution was going to be developing a method of standard for mapping material transportations, phase 4 became shorter than planned from the beginning and more time was spent on further developing concepts, the next phase.
3.5 Concept Development
The generated solutions from the previous phase were developed based on theory from the literature study. This was done in two steps.
The first step, identifying a best practice and standard method for mapping internal trans- portations, was made continuously throughout the mapping process, so when the flow was mapped, more knowledge on how to determine best practice was discovered.
When the mapping was done the method of standard was determined and documented. Step two, presenting what actions Trimble needed to take in order to be able to solve the identified problems from the mapping and implement identified solutions, was made after the mapping.
3.6 Implementation
Since the project was set to be carried out in 20 weeks, implementation did not occur during the lifespan of this project. Suggestions for implementation were presented to Trimble but the practical results of said improvements after implementation were not recorded since they occurred outside of the project.
Instead, a plan for how Trimble could implement solutions and suggestions was developed and presented as the next step for Trimble. The effects of the implementations was discussed with supervisors and reflected upon. The implementation plan for Trimble was divided into different steps and both long term and short term implementation suggestions were made.
3.7 Reliability and Validity
When conducting a research project, it is important to discuss reliability and validity through- out the course of the project (Saunders et al., 2009). Reliability refers to collected data giving consistent results, meaning that when data is collected with the same methods repeated, and the results corresponds to earlier data, the reliability is high (Carmines & Zeller, 1979).
Carmines and Zeller (1979) also explains validity as the ability to collect relevant data with regard to the context. There are two rules to keep in mind when talking about reliability versus validity and that is that high reliability does not guarantee high validity, however, high validity requires high reliability (Saunders et al., 2009).
Risk factors associated with reliability and validity are important to keep in mind so as to avoid in order to keep the reliability and validity high, those factors are:
• Participant error
• Participant bias
• Observer error
• Observer bias
To ensure that risk factors were avoided a lot of focus and attention has been on the data and information gathered from Agile, the internal database and system for Trimble handling all the instrument and their included components and subassemblies .
This eliminates both participant error, participant bias and observer bias since the data is qualitative and thus easier to objectively analyse, which in turn increases the reliability (Saunders et al., 2009).
For the data collected from interviews and observations, the interviews have been recorded so that analysis could be made afterwards, thus lowering the risk of observer bias. The ob- jects being interviewed know beforehand that they are anonymous and before the interview starts, purpose and goal is explained and recorded. Observations have been made in con- sultation with supervisors to ensure the right data is collected and thereby ensuring higher validity.
4 Results of Empirical Execution
Chapter 4, Empirical Execution, will present the empirical results of the current state anal- ysis. For this project that covers the mapped flow of material in production, the routes for transportations of material in production and total time, distance and frequency of mapped material transports.
4.1 The S7 model
The S7 model is made up of three main parts shown in Figure 3. Where number 1 represents the basepart, where the body of the instrument is mounted onto, number 2 the body of the instrument, called the alidad and finally number 3, the telescope.
Figure 3: S7 instrument with marked main parts.
The basepart of the S7 instrument is manufactured right next to the final assembly line in the factory. After manufacturing, the finished base is placed onto material carts placed between final assembly and basepart assembly. From here, the basepart is collected when needed in the final assembly process.
The part of the instrument called the alidad, is assembled in final assembly where han- dles, panel and covers are mounted together with the basepart and the telescope. Figure 4 shows the process description for the S7 instrument. Here the finished telescope collected from the telescope assembly line is mounted into the finished instrument.
Figure 4: Process description of S7 final assembly.
For this project, the telescope of the S7 instrument was chosen to be mapped which is motivated and presented in the next section.
4.2 Mapping of Material Flow
The current state analysis was conducted on a limited part of the material flow. This limita- tion was made early on in the project to ensure that a thorough mapping could be performed in the set time frame for the thesis project.
The chosen part of the S7 instrument was the telescope and it’s belonging subassemblies since the telescope contains parts from all the different manufacturing departments. This will enable the mapping to cover enough of the flow to be relevant. The telescope contains nine subassemblies, all delivered from different manufacturing departments to the telescope assembly line (see Figure 5). These numbers are the referral number used to refer to a certain
subassembly.
During the current state analysis a method for mapping the flow of material through the manufacturing process and their individual transportation routes through production was developed.
To gain enough data relevant for the mapping focus was made on the following variables:
• Frequency of transportation (how many times per day is material being transported)
• Distance (how far is material being transported)
• Time (how much time is being spent on transporting material)
The results were then compiled into a Table showing both distance and time for each depart- ments internal transportations needed for the telescope to be manufactured and expressed in a total time and total distance for daily transport.
For this chapter, the transportation routes mapped will be explained and showed, how the developed method for mapping works and the results of the mapping with identified problem areas.
As stated in the methodology, the method for mapping the flow was a combination between observations, interviews and information in the form of a BOM from Agile. This resulted in a standard method of mapping that can be applied on larger areas of the production at Trimble.
By studying the BOM for the telescope where each subassembly is listed showing what com- ponents the subassembly consists of (with associated article number), in what department manufacturing occurs and where the subassembly is delivered to for further manufacturing, the material flow could be mapped and expressed visually in charts.
The visual charts created are similar to the spaghetti charts method, presented in the theory section, where each line represents a transport of material. However, since the distance and routes differ for each subassembly, the chart only indicates where some sort of transport is made and is not representative for how far or how time consuming each transport is.
This is to create an overview of how complicated the flow is and present the possibility of investigating each individual transport further for Trimble.
The chart shown in Figure 5 shows the nine large subassemblies that an S7 telescope contain with name and department of manufacturing. In the Figure, subassembly one and six are marked red, this is since they have the most complicated subassemblies and consists of most components from different departments and are therefore of higher interest to map.
Figure 5: Chart of included subassemblies for S7 Telescope with department of manufactur- ing.
Based on the complicated flow that was identified and discussions with supervisors, subassem- blies 1, the Telescope DR PLS Vision Pre-Assy and 6, EDM 300 SIRIUS were investigated further for this project.
The compiled chart for all subassemblies is shown in Figure 6 with each line representing a transportation of material, either within the same department or between different depart- ments. Each number shown in the Figure is connected to a subassembly and is compiled into a Table that connects each number in the chart to the right article number.
Figure 6: Visual chart of subassemblies with their routes of transport.
For subassembly number one, Telescope DR PLS Vision Pre-Assy, further mapping was done, applying the same method used for the larger scale mapping. Figure 7 shows the visual result of the mapping for assembly one, Telescope DR PLS Vision Pre-Assy with all containing subassemblies. The dark blue boxes in the Figure represent material delivered straight from the warehouse, meaning components that are not manufactured at Trimble such as screws, sealings and lenses etc. for the instruments. The light blue boxes represent subassemblies that are manufactured at Trimble at the different manufacturing departments.
Appendix C presents a complementary Table presenting the number in chart with associated article number, name of subassembly and department of manufacturing.
Figure 7: Visual chart of subassembly 1 and routes for transport.
The same mapping was done for subassembly 6, the EDM-module, and in Figure 8 the results are presented in the visual chart. Appendix D presents the data belonging to the visual chart.
Figure 8: Visual chart of subassembly 6 and routes for transport.
4.3 Mapping of Transportation
When the transport routes had been identified for the subassemblies of the telescope, it was concluded that a lot of material was transported at the same time to and from the same department, to minimize the amount of transportation. This made it more relevant for the project to map each department of manufacturings individual transportation of the sub- assemblies.
This section describes the flow of material transports, from warehouse, through the man- ufacturing process, all the way to delivery of a subassembly to the telescope assembly line for each department, connected to the subassemblies from Figure 5.
For each department, a Table is compiled presenting results on the variables used for the mapping, meaning frequency, distance and time.
The distance have been measured from building drawings and translated into meters, based on the scale of the drawings. From this the time could be calculated using the average ve- locity and the measured distance from the drawings.
The operator referred to as the material handler in the section is responsible for handling all material for their respective department. There is one for every department making sure the right material is collected from the warehouse based of the order in the internal material planning system called Oracle, that the material gets delivered to the next department in time and that all manufacturing stations in their department is ready for the next order to be manufactured. Oracle is Trimble material handling system and shows all information pertaining material necessary for the daily manufacturing.
For the next subsection, the result of the mapping of the material flow and transportation for each department is presented.
4.3.1 Optics
The optics department, located on the bottom floor of the building, manufactures the Tele- scope DR PLS Vision Pre-Assy with containing components (referral number 1 in Figure 5) for telescopes.
All material is collected from the warehouse, where the material handler orders material needed for the daily manufacturing. The order is placed in the internal material handling system Oracle. Here all information regarding daily manufacturing, batch sizes and material in stock can be found. Based of the order from Oracle the warehouse staff collects the ma- terial specified from Oracle and places it onto material carts that are stationed outside the warehouse gates as shown in Figure 9. When the order is assembled, the material handler transports the cart to the optics department manually through the factory.
Figure 9: Material cart outside warehouse.
From the optics department, material for subassembly 1 is transported to be washed before being assembled into the next subassembly. The washing area is located on the second floor and transportation to the room is made twice a day, one for plasma washing and one for disinfectant washing.
Material is also transported when the final assembly and manufacturing is done for sub- assembly 1, Telescope DR PLS Vision Pre-Assy, and the finished subassemblies are then transported to the telescope line from the optics room.
For subassembly 6, EDM 300 SIRIUS, transport to EDM department is made once a day from the optics department, separate from the transport made to the telescope line.
The visual transportations routes to and from the optics department are shown in Figure 10, with each line representing a transport of material connected to the two subassemblies, 1 and 6.
Figure 10: Transportation Route for Material to and from Optics.
In Table 2 below, the result and data from the mapping is presented. The final column, Double Transport, indicates if the operator transporting the material also have to travel the same route back after the material is delivered. This is an indicator that material handlers spend time on extra motion when collecting or returning empty material carts. This is taken into consideration when calculating how much time operators spend on transportations daily.
This table is used as an reference for the analysis made in the next chapter.
Table 2: Frequency, Time and Distance for Transports in Optics Department
Type Frequency
[times/day]
Total Dis- tance [m]
Total Time [sec]
Double Transport Material for Daily
Manufacturing
1 48 133.33 YES
Washing of Compo- nents
2 50 175.56 YES
Pick-up of Washed Components
2 50 175.56 YES
Delivery to Telescope Line
3 102 293.33 YES
4.3.2 Accessories
Accessories, also referred to as the pre-assembly department, is located on the bottom floor of the factory building but on the other end from optics. They manufacture the chassis and motor that is a part of assembly structure 1.
The material handler orders the material needed for the daily manufacturing from Oracle and the warehouse places it on material carts in the same procedure as for optics. The material handler collects the cart and transport it back to the accessories department as shown in Figure 11
Figure 11: Transportation Route for Material to and from Accessories.
Whenever a pre-assembly is ready after manufacturing, it is placed onto material carts like the one in Figure 9. When a full order of pre-assemblies is ready, it is delivered back to the warehouse for storage until the optics department collects the order for manufacturing.
Besides delivering material to the warehouse for storage, material is delivered to EDM de- partment. Only one type item is delivered, the greywedge (referral number 6.3 in Appendix), in batches that requires delivery every 2.5 day. This delivery is made together with deliv- ery to the warehouse, affecting the distance of transportation for deliveries every 2.5 day.
The results of the collected data from the mapping are compiled in Table 3 and presented below.
